Triple
T6041602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Administration of the Philippines as military governor |
E134557
|
entity |
| Predicate | describesOffice |
P68334
|
FINISHED |
| Object | U.S. military governor of the Philippines |
—
|
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: U.S. military governor of the Philippines | Statement: [Administration of the Philippines as military governor, describesOffice, U.S. military governor of the Philippines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: describesOffice Context triple: [Administration of the Philippines as military governor, describesOffice, U.S. military governor of the Philippines]
-
A.
specifiesOffice
Indicates that an entity is assigned to or associated with a particular office or official position.
-
B.
officeIsIn
Indicates that one office is located within or inside another specified place or building.
-
C.
officeUnder
Indicates that one office is subordinate to, managed by, or organizationally within the authority of another office.
-
D.
officeItAbbreviatesRole
Indicates that an office title or designation serves as an abbreviation for a particular role or position.
-
E.
officeName
Indicates the official name assigned to an office or workplace.
- F. None of above. chosen
Provenance (4 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_69c00875db5c819099dd5bb833ec43c2 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056d11370819096ac35349bd91f4e |
completed | March 22, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69c049eb52a08190ac10fd703735f5aa |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8d4a148190bd8f95caae978e1b |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:08 p.m.