Triple
T17999797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luchino |
E430596
|
entity |
| Predicate | associatedFieldViaNotableBearer |
P106126
|
FINISHED |
| Object | film directing |
—
|
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: film directing | Statement: [Luchino, associatedFieldViaNotableBearer, film directing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedFieldViaNotableBearer Context triple: [Luchino, associatedFieldViaNotableBearer, film directing]
-
A.
hasNotableFieldOfBearers
Indicates that the entities share a significant or distinguished area of activity, expertise, or achievement associated with their bearers.
-
B.
notableField
Indicates the field, discipline, or area of activity for which an entity is especially known or distinguished.
-
C.
associatedWithNotableBearerNationality
Indicates that an entity is connected to the nationality of a notable bearer of a related name or title.
-
D.
associatedWithRoleOfNameBearer
Indicates that an entity is connected to or involved with the specific role or function held by a designated name bearer.
-
E.
fieldOfNotableBearer
chosen
Indicates the professional or activity domain in which a notable bearer of a name, title, or identifier is recognized.
- 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b3e75e908190a6ff6a3ec6069ff5 |
completed | April 19, 2026, 10:52 a.m. |
| PD | Predicate disambiguation | batch_69e3f90039e4819080527f860dca042e |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:23 a.m.