Triple
T16712595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2013 NBA Finals |
E406143
|
entity |
| Predicate | championTitleCountFranchise |
P124323
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [2013 NBA Finals, championTitleCountFranchise, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: championTitleCountFranchise Context triple: [2013 NBA Finals, championTitleCountFranchise, 3]
-
A.
consecutiveTitlesForChampion
Indicates that a champion has won multiple titles in succession without interruption.
-
B.
numberOfTropheeDesChampionsTitles
Indicates the number of Trophée des Champions titles that an entity has won.
-
C.
championTitleCountSinceMoveToSanFrancisco
Indicates the number of championship titles an entity has won since relocating to San Francisco.
-
D.
championConsecutiveTitlesStart
Indicates the point in time or event at which an entity begins a streak of winning championship titles in consecutive editions of a competition.
-
E.
championTitleCountForCanada
Indicates the number of championship titles that have been won on behalf of Canada.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e386530d9c8190b91ec3aac7dc2518 |
completed | April 18, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69e319c379f88190ac0adf812486f598 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326b9e84881909a9166e65bd850d6 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:20 a.m.