Triple
T12558143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Calzaghe |
E295270
|
entity |
| Predicate | finalProfessionalFightYear |
P105892
|
FINISHED |
| Object | 2008 |
—
|
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: 2008 | Statement: [Joe Calzaghe, finalProfessionalFightYear, 2008]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: finalProfessionalFightYear Context triple: [Joe Calzaghe, finalProfessionalFightYear, 2008]
-
A.
lastProfessionalFightDate
Indicates the calendar date on which an entity most recently participated in a professional fight.
-
B.
professionalMMAStartYear
Indicates the calendar year in which an individual began competing in professional mixed martial arts.
-
C.
UFCDebutYear
Indicates the year in which an entity first appeared or made its debut in the UFC.
-
D.
yearsActiveAsBoxer
Indicates the span of time, measured in years, during which an individual was actively engaged in boxing.
-
E.
numberOfProfessionalFights
Indicates the total count of professional-level fights associated with an entity (such as a person or competitor).
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d95410d0b0819097646edd1b837104 |
completed | April 10, 2026, 7:48 p.m. |
| PDg | Predicate description generation | batch_69d95f5148948190946a575d812b329d |
completed | April 10, 2026, 8:36 p.m. |
Created at: April 8, 2026, 11:48 p.m.