Triple
T12653180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TSN2 |
E302215
|
entity |
| Predicate | network |
P2637
|
FINISHED |
| Object | TSN |
E99215
|
NE FINISHED |
How this triple was built (2 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: TSN | Statement: [TSN2, network, TSN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TSN Context triple: [TSN2, network, TSN]
-
A.
TSN
chosen
TSN is a set of IEEE Ethernet standards that enable deterministic, low-latency, and reliable communication for real-time and industrial networking applications.
-
B.
TSN
TSN is the IATA airport code for Tianjin Binhai International Airport, the main air gateway serving the city of Tianjin in northern China.
-
C.
TSN
TSN is a major Canadian English-language sports television network known for broadcasting a wide range of professional and collegiate sports, including NBA games and other premier events.
-
D.
TSN
TSN is the stock ticker symbol for Tyson Foods, Inc., a major American multinational food company known primarily for its meat processing and poultry products.
-
E.
SNY
SNY is a regional sports television network best known as the primary broadcaster of New York Mets games and related sports programming.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96160730c81909e1aa3efb51bf159 |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6719c18508190a9c28b2526e6b336 |
completed | May 2, 2026, 9:50 p.m. |
Created at: April 9, 2026, 5:18 p.m.