Triple
T38231576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Commission on Human Rights of the Philippines |
E1013502
|
entity |
| Predicate | hasCommissionerCount |
P21525
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Commission on Human Rights of the Philippines, hasCommissionerCount, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommissionerCount Context triple: [Commission on Human Rights of the Philippines, hasCommissionerCount, 5]
-
A.
numberOfCommissioners
chosen
Indicates the specific count of commissioners associated with a given entity or context.
-
B.
hasCountyCommissioners
Indicates that an entity is governed or overseen by one or more county commissioners.
-
C.
numberOfResidentCommissioners
Indicates the quantity of resident commissioners associated with a given entity.
-
D.
maximumNumberOfCommissioners
Indicates the upper limit on how many commissioners are allowed in a given governing body or context.
-
E.
hasNumberOfDeputies
Indicates the specific count of deputies associated with or assigned to an entity.
- 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_69f76dd72a248190a5fe18db2bd1eb15 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:30 p.m.