Triple
T4177376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magnite |
E86509
|
entity |
| Predicate | formedByMergerOf |
P77
|
FINISHED |
| Object |
Telaria
Telaria was a video advertising and monetization technology company specializing in connected TV and premium video inventory.
|
E416853
|
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: Telaria | Statement: [Magnite, formedByMergerOf, Telaria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Telaria Context triple: [Magnite, formedByMergerOf, Telaria]
-
A.
Telchinia
Telchinia is the ancient name of the Greek city-state later known as Sicyon, located in the northern Peloponnese.
-
B.
Tholaria
Tholaria is a traditional hillside village on the Greek island of Amorgos, known for its Cycladic architecture and views over Aegiali Bay.
-
C.
Tynaarlo
Tynaarlo is a municipality in the northeastern Netherlands known for its rural character and location between the cities of Groningen and Assen.
-
D.
Teroenza
Teroenza is a character in the Star Wars universe known for being one of the earlier owners of the iconic starship Millennium Falcon.
-
E.
Teurnia
Teurnia was an important ancient Roman city that served as a major administrative and cultural center in the province of Noricum, located in what is now southern Austria.
- 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: Telaria Triple: [Magnite, formedByMergerOf, Telaria]
Generated description
Telaria was a video advertising and monetization technology company specializing in connected TV and premium video inventory.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Telaria Target entity description: Telaria was a video advertising and monetization technology company specializing in connected TV and premium video inventory.
-
A.
Telchinia
Telchinia is the ancient name of the Greek city-state later known as Sicyon, located in the northern Peloponnese.
-
B.
Tholaria
Tholaria is a traditional hillside village on the Greek island of Amorgos, known for its Cycladic architecture and views over Aegiali Bay.
-
C.
Tynaarlo
Tynaarlo is a municipality in the northeastern Netherlands known for its rural character and location between the cities of Groningen and Assen.
-
D.
Teroenza
Teroenza is a character in the Star Wars universe known for being one of the earlier owners of the iconic starship Millennium Falcon.
-
E.
Teurnia
Teurnia was an important ancient Roman city that served as a major administrative and cultural center in the province of Noricum, located in what is now southern Austria.
- 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_69aed93de98c8190ad838ce507b77c8a |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02ec20fc8190b6f30576337e0ddc |
completed | March 9, 2026, 5:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f57509881909d0353a48d868f5d |
completed | March 14, 2026, 3:31 p.m. |
| NEDg | Description generation | batch_69b57fbb037481908b2891e3af32e6e5 |
completed | March 14, 2026, 3:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b58016777c8190a3e73ab96907e3a3 |
completed | March 14, 2026, 3:34 p.m. |
Created at: March 9, 2026, 3:45 p.m.