Triple
T28870673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Rivalry |
E732131
|
entity |
| Predicate | notableGameNumber |
P203533
|
FINISHED |
| Object | 150th meeting |
—
|
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: 150th meeting | Statement: [The Rivalry, notableGameNumber, 150th meeting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableGameNumber Context triple: [The Rivalry, notableGameNumber, 150th meeting]
-
A.
notableGame
Indicates that a particular game is especially significant, prominent, or well-known in relation to the associated entity.
-
B.
notableGameRound
Indicates that a particular game round is especially significant or noteworthy within the context of the game or competition.
-
C.
notableGameEvent
Indicates that a specific game is associated with a significant or noteworthy event in its history or context.
-
D.
dateOfNotableGame
Indicates the calendar date on which a particular notable game took place.
-
E.
notableGameLine
Indicates that a particular line of dialogue or text is especially notable or significant within a game.
- 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_69f05b06807c81909b4bbd4c20403a2b |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_6a019dfc69fc8190b0d80279a6216ba7 |
completed | May 11, 2026, 9:14 a.m. |
| PD | Predicate disambiguation | batch_6a019d54586c81908292d4880db9fad2 |
completed | May 11, 2026, 9:11 a.m. |
| PDg | Predicate description generation | batch_6a019dfba430819089f5609d89fbb7d9 |
completed | May 11, 2026, 9:14 a.m. |
Created at: April 28, 2026, 7:32 a.m.