Triple
T10192253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siquijor |
E238064
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Larena |
E559095
|
NE 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: Larena | Statement: [Siquijor, hasMunicipality, Larena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Larena Context triple: [Siquijor, hasMunicipality, Larena]
-
A.
Larena
chosen
Larena is a coastal municipality on Siquijor Island in the Philippines known historically as a key commercial and educational center of the province.
-
B.
Latorica
Latorica is a river in Central Europe that flows through western Ukraine and eastern Slovakia, forming part of the Tisza River basin.
-
C.
Lakalai
Lakalai is an Oceanic language spoken by an indigenous community in Papua New Guinea.
-
D.
Laiolo
Laiolo is an alternate name for the Laiyolo language, an Austronesian language spoken in parts of Indonesia.
-
E.
Palena
Palena is a small town and municipality in the Palena Province of Chile’s Los Lagos Region, known for its remote Andean landscapes and outdoor tourism.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca84de1b208190bf17bb305b002605 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdedc4fb808190aae2e4b84be96f83 |
completed | April 2, 2026, 4:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d317ca2cf481909cf715ef9248be3c |
completed | April 6, 2026, 2:17 a.m. |
Created at: March 30, 2026, 9:13 p.m.