Triple
T1644721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gangseo District |
E35554
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Noksan Industrial Complex |
E157612
|
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: Noksan Industrial Complex | Statement: [Gangseo District, contains, Noksan Industrial Complex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noksan Industrial Complex Context triple: [Gangseo District, contains, Noksan Industrial Complex]
-
A.
Onsan National Industrial Complex
Onsan National Industrial Complex is a major South Korean industrial zone in Ulsan known for its large-scale petrochemical, metal, and heavy manufacturing facilities.
-
B.
Hedley Industrial Complex
The Hedley Industrial Complex is a historic former manufacturing site in Troy, New York, that has been redeveloped into a mixed-use commercial and office complex along the Hudson River.
-
C.
Sasang Industrial Complex
chosen
Sasang Industrial Complex is a major manufacturing and logistics hub in Busan, South Korea, housing a dense concentration of factories and industrial facilities.
-
D.
Yokkaichi Industrial Complex
Yokkaichi Industrial Complex is a major Japanese petrochemical and heavy industrial zone known for its large-scale refineries, chemical plants, and historical impact on environmental policy.
-
E.
SIVA chemical factory
SIVA chemical factory was an Italian industrial plant where writer and chemist Primo Levi worked as a chemist after surviving World War II.
- 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_69a88604618c81908b41f6429c431eb6 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa622e9b08819094960b2329c6e7e6 |
completed | March 6, 2026, 5:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad60a26350819087e7a87b52561143 |
completed | March 8, 2026, 11:42 a.m. |
Created at: March 4, 2026, 7:28 p.m.