Triple
T7902370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dexter Henson |
E183483
|
entity |
| Predicate | fatherFormerOccupation |
P2600
|
FINISHED |
| Object | professional rugby player |
—
|
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: professional rugby player | Statement: [Dexter Henson, fatherFormerOccupation, professional rugby player]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fatherFormerOccupation Context triple: [Dexter Henson, fatherFormerOccupation, professional rugby player]
-
A.
fatherOccupation
chosen
Indicates the type of job or profession held by a person's father.
-
B.
characterFormerOccupation
Indicates that a character previously held a specific occupation but no longer does.
-
C.
parentOccupation
Indicates that one entity has an occupation which is the job or profession of the other entity’s parent.
-
D.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
-
E.
sonOccupation
Indicates that a specified occupation is the job or professional role held by a person's son.
- 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_69ca828d13088190b222be7aa9f9315c |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a40a0508190864479c2c41b12cb |
completed | March 31, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69cae92d94448190b4425bbfb64c658c |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:02 p.m.