Triple
T29432515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hussein Dey |
E746471
|
entity |
| Predicate | flyWhiskIncidentRole |
P167167
|
FINISHED |
| Object | alleged striker of the French consul |
—
|
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: alleged striker of the French consul | Statement: [Hussein Dey, flyWhiskIncidentRole, alleged striker of the French consul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flyWhiskIncidentRole Context triple: [Hussein Dey, flyWhiskIncidentRole, alleged striker of the French consul]
-
A.
farePolicyRole
Indicates the role or function an entity has within a fare policy, such as how it participates in defining, applying, or managing that policy.
-
B.
wingOf
Indicates that something is a wing that forms a physical or functional part of another entity.
-
C.
skyRole
Indicates a role or function that an entity has specifically in relation to the sky or sky-related phenomena.
-
D.
wingNumber
Indicates the specific identifier or count assigned to a wing associated with an entity.
-
E.
fliesFlag
Indicates that one entity displays or hoists the flag of another entity, symbolically representing affiliation, identity, or allegiance.
- 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_69f0a7a06e0081908add494075912eb4 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f66aca488081909c41adff321b3a48 |
completed | May 2, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69f66339175c819080bd70f0ff7057b1 |
completed | May 2, 2026, 8:48 p.m. |
| PDg | Predicate description generation | batch_69f663ff176c8190aaadb475f75daee4 |
completed | May 2, 2026, 8:52 p.m. |
Created at: April 28, 2026, 3:14 p.m.