Triple
T18435618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Makati, Michigan (historical relationship) |
E450382
|
entity |
| Predicate | involvesName |
P1256
|
FINISHED |
| Object | Makati |
—
|
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: Makati | Statement: [Makati, Michigan (historical relationship), involvesName, Makati]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvesName Context triple: [Makati, Michigan (historical relationship), involvesName, Makati]
-
A.
namedIn
Indicates that one entity is explicitly mentioned or referenced by name within another entity (such as a document, statement, or record).
-
B.
involves
chosen
Indicates that an entity participates in, is a part of, or is implicated within a particular event, process, or relationship.
-
C.
nameOf
Indicates that one entity is the name or designation of another entity.
-
D.
mayBeInvolvedIn
Indicates that an entity has a possible, but not certain, participation or role in a particular event, activity, or situation.
-
E.
usesNameDueTo
Indicates that one entity adopts or applies a particular name for another entity specifically because of some motivating reason, circumstance, or dependency.
- 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_69d8d381d6388190a9e94e9c658174e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51c0bd35c8190b66d62ad9987377f |
completed | April 19, 2026, 6:16 p.m. |
| PD | Predicate disambiguation | batch_69e469c943a4819094c8fdc5971ad3a7 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:28 a.m.