Triple
T30694248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McNeese State Cowboys football |
E781411
|
entity |
| Predicate | stadiumNickname |
P9350
|
FINISHED |
| Object |
The Hole
The Hole is the colloquial nickname for the home football stadium of the McNeese State Cowboys, known for its intense atmosphere and passionate fan base.
|
E1927282
|
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: The Hole | Statement: [McNeese State Cowboys football, stadiumNickname, The Hole]
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: The Hole Triple: [McNeese State Cowboys football, stadiumNickname, The Hole]
Generated description
The Hole is the colloquial nickname for the home football stadium of the McNeese State Cowboys, known for its intense atmosphere and passionate fan base.
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_69f224ab24e08190991d6edb6df58e8b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68bda88048190bdd6992094c7644d |
completed | May 2, 2026, 11:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a287111ec348190ada26cf726bafe78 |
completed | June 9, 2026, 8:01 p.m. |
| NEDg | Description generation | batch_6a2875e84bf881909c837b369a1b3c97 |
completed | June 9, 2026, 8:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a28766648b081909025200756061c34 |
completed | June 9, 2026, 8:24 p.m. |
Created at: April 29, 2026, 8:33 p.m.