Triple
T19500199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sugar Capital of the Philippines |
E487881
|
entity |
| Predicate | sectorLinked |
P47145
|
FINISHED |
| Object | agriculture |
—
|
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: agriculture | Statement: [Sugar Capital of the Philippines, sectorLinked, agriculture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectorLinked Context triple: [Sugar Capital of the Philippines, sectorLinked, agriculture]
-
A.
sector
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
-
B.
sectorInfluence
Indicates the degree to which one sector affects, shapes, or exerts control over another sector or over outcomes within that sector.
-
C.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
D.
sectoralCoverage
Indicates the specific sectors, industries, or domains to which something (such as a policy, agreement, or dataset) applies or extends.
-
E.
associatedWithEconomicSector
chosen
Indicates that an entity has a connection or involvement with a particular economic sector, such as operating, participating, or being relevant within that sector.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6350ce7cc819086d77bbd9cd52b53 |
completed | April 20, 2026, 2:15 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7bd25881908caa04eaef1f6718 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:40 p.m.