Triple
T17175730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telaria |
E416853
|
entity |
| Predicate | tickerSymbol |
P1447
|
FINISHED |
| Object |
TLRA
TLRA was the stock ticker symbol for Telaria, a video advertising and monetization technology company that operated a programmatic platform for connected TV and digital video.
|
E1254565
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: TLRA | Statement: [Telaria, tickerSymbol, TLRA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TLRA Context triple: [Telaria, tickerSymbol, TLRA]
-
A.
TLA
TLA is a formal specification language developed by Leslie Lamport for describing and reasoning about concurrent and distributed systems using temporal logic.
-
B.
RTRA
RTRA is the abbreviation for the Royal Tank Regiment Association, an organization that supports and connects current and former members of the Royal Tank Regiment.
-
C.
TL
TL is the vehicle registration code used on license plates for vehicles registered in Tulcea County, Romania.
-
D.
TL
TL is the public transport operator serving the Lausanne region in Switzerland, managing the city’s metro, bus, and related transit services.
-
E.
T&L
T&L is the common abbreviation for Tate & Lyle, a British multinational agribusiness and food ingredients company best known for producing sweeteners and other specialty food ingredients.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: TLRA Triple: [Telaria, tickerSymbol, TLRA]
Generated description
TLRA was the stock ticker symbol for Telaria, a video advertising and monetization technology company that operated a programmatic platform for connected TV and digital video.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TLRA Target entity description: TLRA was the stock ticker symbol for Telaria, a video advertising and monetization technology company that operated a programmatic platform for connected TV and digital video.
-
A.
TLA
TLA is a formal specification language developed by Leslie Lamport for describing and reasoning about concurrent and distributed systems using temporal logic.
-
B.
RTRA
RTRA is the abbreviation for the Royal Tank Regiment Association, an organization that supports and connects current and former members of the Royal Tank Regiment.
-
C.
TL
TL is the vehicle registration code used on license plates for vehicles registered in Tulcea County, Romania.
-
D.
TL
TL is the public transport operator serving the Lausanne region in Switzerland, managing the city’s metro, bus, and related transit services.
-
E.
T&L
T&L is the common abbreviation for Tate & Lyle, a British multinational agribusiness and food ingredients company best known for producing sweeteners and other specialty food ingredients.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3fc0cec448190b30466628a2ff23f |
completed | April 18, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0148435f6081909bfc6cc1ef59d971 |
completed | May 11, 2026, 3:08 a.m. |
| NEDg | Description generation | batch_6a014a4fdcf081908be68b1eda2066df |
completed | May 11, 2026, 3:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a014adf25808190ad712fbd7560e91d |
completed | May 11, 2026, 3:19 a.m. |
Created at: April 10, 2026, 5:37 a.m.