Triple
T6527890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princeton Tigers men's ice hockey |
E151351
|
entity |
| Predicate | hasLongHistory |
P71432
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [Princeton Tigers men's ice hockey, hasLongHistory, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLongHistory Context triple: [Princeton Tigers men's ice hockey, hasLongHistory, true]
-
A.
hasHistoryPeriod
Indicates that something is associated with, belongs to, or occurs within a specific historical period or era.
-
B.
hasHistoricalContext
Indicates that something is related to, influenced by, or best understood in light of specific past events, conditions, or time periods.
-
C.
hasHistoricalSection
Indicates that something includes a dedicated part or segment that presents historical information or context.
-
D.
hasHistoryOf
Indicates that an entity has a documented prior occurrence or background of a specified condition, event, or state.
-
E.
hasHistoricalCategory
Indicates that something is associated with a particular historical classification, period, or type based on its past context or significance.
- F. None of above. chosen
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_69c687f522748190b3058405553cdabd |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ada9c8408190b1bc327985366be9 |
completed | March 27, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69c68abbc7148190a8270d47fe10cc31 |
completed | March 27, 2026, 1:48 p.m. |
| PDg | Predicate description generation | batch_69c69f362ee4819090e8fa48caef7d7d |
completed | March 27, 2026, 3:16 p.m. |
Created at: March 27, 2026, 1:46 p.m.