Triple
T9743509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MGR Memorial |
E236248
|
entity |
| Predicate | honoursOccupation |
P18120
|
FINISHED |
| Object | film actor |
—
|
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 actor | Statement: [MGR Memorial, honoursOccupation, film actor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: honoursOccupation Context triple: [MGR Memorial, honoursOccupation, film actor]
-
A.
honouredPersonOccupation
chosen
Indicates that the honored person is or was associated with a particular occupation or professional role.
-
B.
honoursPosition
Indicates that one entity holds or is recognized with an honorary or distinguished position in relation to another entity.
-
C.
sonOccupation
Indicates that a specified occupation is the job or professional role held by a person's son.
-
D.
honourOf
Indicates that one entity is the source, bearer, or cause of another entity’s honor, prestige, or distinguished recognition.
-
E.
honoursTitle
Indicates that an entity holds or is designated by a formal honorific or honorary title.
- 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_69ca84d3e24481908a476e2231123cf9 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9f2e5bb081908047e3bf5fe3991c |
completed | April 1, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69cd03cc128c81908b84ef224f858b4e |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:23 p.m.