Triple
T34099121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ohio State Buckeyes football venues |
E874515
|
entity |
| Predicate | notableNicknameVenue |
P113968
|
FINISHED |
| Object | The Horseshoe |
E275691
|
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 Horseshoe | Statement: [Ohio State Buckeyes football venues, notableNicknameVenue, The Horseshoe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableNicknameVenue Context triple: [Ohio State Buckeyes football venues, notableNicknameVenue, The Horseshoe]
-
A.
notableNickname
Indicates that one entity is a well-known or widely recognized nickname or moniker for another entity.
-
B.
notablePlayNickname
Indicates that a particular play or performance is commonly known by a specific nickname.
-
C.
notableVenueFor
chosen
Indicates that a venue is especially recognized or significant for hosting, presenting, or being associated with a particular entity or activity.
-
D.
notableGameNickname
Indicates that an entity is a well-known or commonly used nickname for a particular game.
-
E.
notableRecordingVenueFor
Indicates that a venue is particularly recognized or distinguished as the place where a specific recording was made.
- F. None of above.
Provenance (4 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_69f349a735208190a1dbfb1c2a121059 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a36ae622c448190917e3b269eb76f74 |
completed | June 20, 2026, 3:14 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:53 a.m.