Triple
T19293308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Ship disaster |
E482494
|
entity |
| Predicate | survivorOccupation |
P135155
|
FINISHED |
| Object | butcher |
—
|
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: butcher | Statement: [White Ship disaster, survivorOccupation, butcher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: survivorOccupation Context triple: [White Ship disaster, survivorOccupation, butcher]
-
A.
victimOccupation
Indicates the profession or job role held by the person who is the victim in an event or incident.
-
B.
isSurvivorOf
Indicates that one entity has lived through, endured, or remained alive after a particular event, condition, or harmful circumstance involving another entity.
-
C.
survivorWith
Indicates a relationship where one entity survives an event or condition together with, or in the presence of, another entity.
-
D.
originalHolderOccupation
Indicates the occupation or professional role held by the entity that originally possessed or owned another entity.
-
E.
representedOccupation
Indicates that one entity has served as an official or formal representative of another entity’s occupation or professional role.
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc824b448190865230eed8ef9ebf |
completed | April 20, 2026, 10:14 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0bc7508190a6f9d56bd4c3404f |
completed | April 19, 2026, 1:47 p.m. |
| PDg | Predicate description generation | batch_69e4ddcf50108190a09d0f1291c17374 |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 1:31 p.m.