Triple
T7508627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuas |
E177456
|
entity |
| Predicate | landReclamationPurpose |
P16193
|
FINISHED |
| Object | industrial expansion |
—
|
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: industrial expansion | Statement: [Tuas, landReclamationPurpose, industrial expansion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: landReclamationPurpose Context triple: [Tuas, landReclamationPurpose, industrial expansion]
-
A.
hasLandReclamation
chosen
Indicates that an entity has carried out, is involved in, or is characterized by the process of creating new land from oceans, rivers, or other water bodies.
-
B.
dredgingPurpose
Indicates that an action or process of dredging is carried out for a specified purpose or intended use.
-
C.
purposeOfConstruction
Indicates that one entity was constructed or built in order to serve, enable, or fulfill the function, goal, or intended use represented by another entity.
-
D.
majorLandUse
Indicates the primary way a given area of land is utilized or designated (e.g., residential, commercial, agricultural).
-
E.
otherLandUse
Indicates that the land is used for purposes that do not fall into any of the primary or predefined land-use categories.
- 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_69c69f276b108190af2cc790b6554544 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5b8ab5c8190828ee8d144068828 |
completed | March 27, 2026, 9:25 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d44e9481909813e073b194f6f4 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:45 p.m.