Triple
T28848422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fred Williamson |
E728516
|
entity |
| Predicate | yearsActiveAsFootballPlayer |
P8357
|
FINISHED |
| Object | 1960–1967 |
—
|
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: 1960–1967 | Statement: [Fred Williamson, yearsActiveAsFootballPlayer, 1960–1967]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearsActiveAsFootballPlayer Context triple: [Fred Williamson, yearsActiveAsFootballPlayer, 1960–1967]
-
A.
activeYearsInCareer
Indicates the span of time during which an entity was actively engaged in a particular career or professional field.
-
B.
yearsAsPlayerAtClub
Indicates the number of years a person spent playing for a particular club.
-
C.
activeYearsInSport
chosen
Indicates the span of years during which an entity actively participated in a particular sport.
-
D.
activeYearsInMLS
Indicates the span of years during which an entity was actively involved in Major League Soccer (MLS).
-
E.
activeYearsInWorldCup
Indicates the span of years during which an entity actively participated in World Cup competitions.
- 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_69f0319f4e5481909e4c439dbe8be940 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f659d651e08190bbd11dd3013f849c |
completed | May 2, 2026, 8:08 p.m. |
| PD | Predicate disambiguation | batch_69f65762b5e481908a30ca963dcba4be |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 6:43 a.m.