Triple
T28884225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morotai |
E732506
|
entity |
| Predicate | emergingSector |
P143750
|
FINISHED |
| Object | tourism |
—
|
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: tourism | Statement: [Morotai, emergingSector, tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emergingSector Context triple: [Morotai, emergingSector, tourism]
-
A.
developedSector
Indicates that an entity has contributed to the growth, advancement, or establishment of a particular sector or industry.
-
B.
notableSector
Indicates that an entity is particularly prominent, influential, or significant within a specified sector or industry.
-
C.
technologySectorFeature
Indicates that something is a characteristic, attribute, or defining aspect of the technology sector.
-
D.
innovationArea
Indicates the thematic or domain-specific field in which an innovation is focused or applied.
-
E.
economicSectors
chosen
Indicates a relationship that associates entities with the economic sectors or industries in which they operate or to which they belong.
- 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_69f05b07bdec819080cadfe147aa1f25 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65b14512c8190a40e70319dcc54cd |
completed | May 2, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 7:48 a.m.