Triple
T1601453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Team LeBron |
E34400
|
entity |
| Predicate | targetScoreAfterThreeQuarters |
P30631
|
FINISHED |
| Object | 157 |
—
|
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: 157 | Statement: [Team LeBron, targetScoreAfterThreeQuarters, 157]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetScoreAfterThreeQuarters Context triple: [Team LeBron, targetScoreAfterThreeQuarters, 157]
-
A.
halftimeScore
Indicates the score or result of a game or match at the halfway point (halftime).
-
B.
winningTeamScore
Indicates the number of points or goals achieved by the team that wins a particular game or competition.
-
C.
thirdQuarterLargestLead
Indicates the size of the largest lead one side holds over the other during the third quarter of a game or match.
-
D.
team2Score
Indicates the number of points or goals scored by the second team in a game or competition.
-
E.
targetScoreRule
Indicates the rule or criteria used to determine the target score to be achieved or applied in a given context.
- 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_69a885fea6a481909fe83ba6441f1774 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a95b02cd448190be8e3db9a5a7bac0 |
completed | March 5, 2026, 10:29 a.m. |
| PD | Predicate disambiguation | batch_69a907c1cad08190b9728dd557f39aa0 |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a95aada3f881909053363c01de8b57 |
completed | March 5, 2026, 10:29 a.m. |
Created at: March 4, 2026, 7:28 p.m.