Triple
T13661261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turmeric City |
E326998
|
entity |
| Predicate | commoditySpecialization |
P43327
|
FINISHED |
| Object | spices |
—
|
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: spices | Statement: [Turmeric City, commoditySpecialization, spices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commoditySpecialization Context triple: [Turmeric City, commoditySpecialization, spices]
-
A.
commodityType
Indicates the classification of a good or product according to its type or category within a commodity system.
-
B.
commodityProduced
Indicates that a particular commodity is generated, manufactured, or otherwise produced by a specified entity or process.
-
C.
commodityClass
Indicates that one entity is classified as belonging to a particular category or class of commodities in relation to another entity.
-
D.
marketSpecialization
chosen
Indicates a relationship where an entity focuses its activities, products, or services on serving a specific segment or niche of a broader market.
-
E.
productSpecialization
Indicates that a product is tailored or adapted to meet the specific needs, preferences, or requirements of a particular market segment, use case, or customer group.
- 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc620df208190afaccf3ddd10aa60 |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8a027081908d8f884b89707a5e |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:52 p.m.