Triple
T2857421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lou Gehrig |
E63235
|
entity |
| Predicate | consecutiveGamesRecordHeldFrom |
P43691
|
FINISHED |
| Object | 1933 |
—
|
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: 1933 | Statement: [Lou Gehrig, consecutiveGamesRecordHeldFrom, 1933]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consecutiveGamesRecordHeldFrom Context triple: [Lou Gehrig, consecutiveGamesRecordHeldFrom, 1933]
-
A.
consecutiveGamesPlayed
Indicates that an entity has participated in a series of games without interruption, one immediately following another.
-
B.
mostConsecutiveWinsCount
Indicates the highest number of wins achieved in a row within a given sequence or context.
-
C.
consecutiveWinningSeasons
Indicates that an entity (such as a team or individual) has achieved winning seasons in back-to-back or uninterrupted consecutive years.
-
D.
consecutiveWinsInSeason
Indicates that one entity achieved a specified number of back-to-back victories within a single season.
-
E.
longestUnbeatenStreak
Indicates the relationship where an entity holds the greatest continuous sequence of events (such as games or matches) without a loss compared to others.
- 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_69ab4c41e8c08190a9e8f5249cc12610 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf881bbc81908987317b88b405d0 |
completed | March 7, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69abdd10aef88190b750aae07e7df4dc |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abdee94c2081908e5075e87e70780a |
completed | March 7, 2026, 8:16 a.m. |
Created at: March 6, 2026, 10:02 p.m.