Triple
T24766275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pac-Man |
E619590
|
entity |
| Predicate | nicknameOfOccupation |
P157295
|
FINISHED |
| Object | Philippine senator |
—
|
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: Philippine senator | Statement: [Pac-Man, nicknameOfOccupation, Philippine senator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nicknameOfOccupation Context triple: [Pac-Man, nicknameOfOccupation, Philippine senator]
-
A.
nicknameOfOccupation
chosen
Indicates that one term is an informal or colloquial nickname used to refer to a particular occupation or job role.
-
B.
occupationalNameFor
Indicates that one entity is the name or label used to denote the occupation or profession of another entity.
-
C.
aliasOfOccupation
Indicates that one occupation term is an alternative name or alias for another occupation.
-
D.
associatedNicknameOfWork
Indicates that a given nickname or informal title is commonly used to refer to a particular work.
-
E.
praenomenOfOccupation
Indicates that a given praenomen (personal first name) is used as or associated with a particular occupation.
- 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_69e2fabbea94819092ed41348909622f |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f453035f508190be83a3d521723acf |
completed | May 1, 2026, 7:15 a.m. |
| PD | Predicate disambiguation | batch_69f44d6ef33081908f5d36ba1ae5f473 |
completed | May 1, 2026, 6:51 a.m. |
Created at: April 18, 2026, 4:28 a.m.