Triple
T35537867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albert Goodwill Spalding |
E1026977
|
entity |
| Predicate | won20OrMoreGamesConsecutivelySeasons |
P8065
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Albert Goodwill Spalding, won20OrMoreGamesConsecutivelySeasons, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: won20OrMoreGamesConsecutivelySeasons Context triple: [Albert Goodwill Spalding, won20OrMoreGamesConsecutivelySeasons, 6]
-
A.
consecutiveWinningSeasons
Indicates that an entity (such as a team or individual) has achieved winning seasons in back-to-back or uninterrupted consecutive years.
-
B.
consecutiveWinsInSeason
chosen
Indicates that one entity achieved a specified number of back-to-back victories within a single season.
-
C.
consecutiveGamesRecordHeldFrom
Indicates that one entity held the record for most consecutive games played starting from a specified point in time.
-
D.
consecutiveGamesRecordHeldUntil
Indicates that an entity held the record for most consecutive games until a specified later point in time or event.
-
E.
mostConsecutiveWinsCount
Indicates the highest number of wins achieved in a row within a given sequence 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_69f76dff7e508190b28ceeee770dce23 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79a54aa3c8190b2bb5d790b2d42d4 |
completed | May 3, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69f7961970408190b669cc556e30a608 |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:04 p.m.