Triple
T34962306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1989 NCAA Division I women's basketball championship |
E1008290
|
entity |
| Predicate | hostStateCount |
P182144
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [1989 NCAA Division I women's basketball championship, hostStateCount, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hostStateCount Context triple: [1989 NCAA Division I women's basketball championship, hostStateCount, 12]
-
A.
hostState
Indicates a relationship where one entity serves as the host or governing state for another entity, within whose jurisdiction, territory, or authority that other entity operates or resides.
-
B.
observerStateCount
Indicates the number of distinct states or conditions that an observer entity can occupy or register within the described context.
-
C.
numberOfHosts
Indicates the total count of distinct hosts associated with or involved in a given entity or event.
-
D.
numberOfStates
Indicates the total count of distinct states or conditions associated with an entity or system.
-
E.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
- 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_69f76dc69564819099e9e78aed6ff0a6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78710282c81909146dc0be91e983f |
completed | May 3, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f784162134819098413482ef52042f |
completed | May 3, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69f7870dfe108190996c0c68630edc7f |
completed | May 3, 2026, 5:34 p.m. |
Created at: May 3, 2026, 4 p.m.