Triple
T18569361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bellerive Oval |
E453836
|
entity |
| Predicate | firstFirstClassMatch |
P132581
|
FINISHED |
| Object | 1987 |
—
|
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: 1987 | Statement: [Bellerive Oval, firstFirstClassMatch, 1987]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstFirstClassMatch Context triple: [Bellerive Oval, firstFirstClassMatch, 1987]
-
A.
firstClassMatches
Indicates that the entities are involved in matches or events that are classified as first-class (i.e., officially recognized top-level matches).
-
B.
firstClassRuns
Indicates that the subject has participated in official first-class cricket matches, with the object specifying the number or record of such runs scored.
-
C.
firstFirstClassSeason
Indicates that the referenced season is the first season in which the entity participated in first-class competition.
-
D.
firstClassMatchesPlayed
Indicates the number of first-class cricket matches that an entity has participated in.
-
E.
firstMatchCity
Indicates that the referenced city is the first one that matches a given set of criteria or search conditions among multiple possible cities.
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53b0075a08190a5d590d36089ca1e |
completed | April 19, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69e478c16e0c8190b03966aa23c395a6 |
completed | April 19, 2026, 6:40 a.m. |
| PDg | Predicate description generation | batch_69e484121cd48190bf583b4c94636a30 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 11:43 a.m.