Triple
T18442472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shenzhen metropolitan area |
E450564
|
entity |
| Predicate | innovationEcosystemFeature |
P460
|
FINISHED |
| Object | high concentration of tech firms |
—
|
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: high concentration of tech firms | Statement: [Shenzhen metropolitan area, innovationEcosystemFeature, high concentration of tech firms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: innovationEcosystemFeature Context triple: [Shenzhen metropolitan area, innovationEcosystemFeature, high concentration of tech firms]
-
A.
innovationArea
Indicates the thematic or domain-specific field in which an innovation is focused or applied.
-
B.
innovationLevel
Indicates the degree or extent to which something is new, original, or creatively advanced compared to existing norms or solutions.
-
C.
hasInnovationHub
chosen
Indicates that an entity hosts, contains, or is associated with a dedicated center or facility focused on innovation activities.
-
D.
hasInnovationType
Indicates that an entity is associated with, or classified by, a specific type or category of innovation.
-
E.
innovationFrom
Indicates that something originates, arises, or is derived as an innovation from a particular source or prior entity.
- 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_69d8d381d6388190a9e94e9c658174e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51c11b1288190b9ed4497751197d1 |
completed | April 19, 2026, 6:16 p.m. |
| PD | Predicate disambiguation | batch_69e469c943a4819094c8fdc5971ad3a7 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:30 a.m.