Triple
T2681379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lois Lane |
E56580
|
entity |
| Predicate | professionTrait |
P35550
|
FINISHED |
| Object | Pulitzer Prize–winning reporter |
—
|
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: Pulitzer Prize–winning reporter | Statement: [Lois Lane, professionTrait, Pulitzer Prize–winning reporter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionTrait Context triple: [Lois Lane, professionTrait, Pulitzer Prize–winning reporter]
-
A.
professionalHead
Indicates that one entity serves as the primary professional leader or chief authority over another entity within an organizational or occupational context.
-
B.
memberProfession
chosen
Indicates that a member or individual holds or practices a particular profession or occupation.
-
C.
professional
Indicates that one entity has a formal, occupation-related role, service, or expertise in relation to another entity.
-
D.
professionalSince
Indicates the point in time when an entity began its professional activity or career in a given role or field.
-
E.
portraysProfession
Indicates that one entity depicts or represents another entity in a specific profession or occupational role.
- 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_69ab4a4b13fc81909dfdb3f23da46832 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abda2f7bf88190a1e3103dd014d871 |
completed | March 7, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69abd81ab9d08190b72b6104c6dbc769 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.