Triple
T23892187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shenzhou City |
E600797
|
entity |
| Predicate | hasDevelopingSector |
P95526
|
FINISHED |
| Object | local industry |
—
|
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: local industry | Statement: [Shenzhou City, hasDevelopingSector, local industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDevelopingSector Context triple: [Shenzhou City, hasDevelopingSector, local industry]
-
A.
developedSector
Indicates that an entity has contributed to the growth, advancement, or establishment of a particular sector or industry.
-
B.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
C.
hasGrowingSector
chosen
Indicates that a particular sector or industry is experiencing growth or expansion over time.
-
D.
hasEconomicDevelopment
Indicates that one entity possesses, experiences, or is characterized by a certain level or type of economic growth, progress, or improvement in its economic conditions.
-
E.
hasIndustrialDevelopment
Indicates that an entity possesses, supports, or is characterized by industrial growth, infrastructure, or manufacturing-related development.
- 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_69e295341ac0819080647f2908af793c |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cd044708819091102ecc160e1961 |
completed | April 29, 2026, 9:19 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:25 p.m.