Triple
T6839681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waray people |
E157539
|
entity |
| Predicate | primaryAreaInLeyte |
P19488
|
FINISHED |
| Object | northeastern Leyte |
—
|
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: northeastern Leyte | Statement: [Waray people, primaryAreaInLeyte, northeastern Leyte]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryAreaInLeyte Context triple: [Waray people, primaryAreaInLeyte, northeastern Leyte]
-
A.
primaryArea
chosen
Indicates that one entity is the main or most important area, domain, or field associated with another entity.
-
B.
rankByAreaInPhilippines
Indicates the relative ordering of entities based on their area size specifically within the Philippines.
-
C.
primarySurveyArea
Indicates that a specified area is the main or principal region targeted or covered by a particular survey or data collection activity.
-
D.
hasNumberOfBarangays
Indicates the total count of barangays associated with a given administrative unit or locality.
-
E.
barangay
Indicates that an entity is associated with, located in, or falls under the jurisdiction of a specific barangay (the smallest local administrative division).
- 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_69c6882c53608190b99aebef079b23bd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d6b2ee248190991c3e827be75bb7 |
completed | March 27, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69c6d09f90648190bc0a462c7d59de1b |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:19 p.m.