Triple
T21281263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Tavares |
E524528
|
entity |
| Predicate | totalNLLPoints |
P17024
|
FINISHED |
| Object | over 1700 |
—
|
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: over 1700 | Statement: [John Tavares, totalNLLPoints, over 1700]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalNLLPoints Context triple: [John Tavares, totalNLLPoints, over 1700]
-
A.
hasLogLikelihood
Indicates that a particular outcome, event, or data instance is associated with a specified numerical value representing the logarithm of its probability (log-likelihood) under a given model or distribution.
-
B.
totalPointsScored
chosen
Indicates the total number of points accumulated or scored by an entity over a defined period, event, or context.
-
C.
pointsForRegulationLoss
Indicates the number of points awarded to a team or player specifically for losing a game in regulation time.
-
D.
hasNumberOfPoints
Indicates that an entity is associated with a specific count of points it possesses or comprises.
-
E.
numberOfSurveyPoints
Indicates the total count of survey points associated with a given entity or context.
- F. None of above.
Provenance (3 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_69e0b5171f6c8190a5d57201ede73811 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e736d186988190a5b16fcb669ece9f |
completed | April 21, 2026, 8:35 a.m. |
| PD | Predicate disambiguation | batch_69e5f6161dac8190b06009cd180e3ff7 |
completed | April 20, 2026, 9:47 a.m. |
Created at: April 16, 2026, 4:02 p.m.