Triple
T29611596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Light Industrial Area Bhilai |
E754737
|
entity |
| Predicate | typicalEnterpriseSize |
P145324
|
FINISHED |
| Object | small and medium enterprises |
—
|
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: small and medium enterprises | Statement: [Light Industrial Area Bhilai, typicalEnterpriseSize, small and medium enterprises]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalEnterpriseSize Context triple: [Light Industrial Area Bhilai, typicalEnterpriseSize, small and medium enterprises]
-
A.
typicalCompanySize
Indicates the usual or most common number of employees associated with a company.
-
B.
typicalEnterprises
Indicates that an entity is a standard or representative example of enterprises within a given context or category.
-
C.
typicalTeamSize
Indicates the usual or most common number of members that make up a given team.
-
D.
associatedWithCompanySize
chosen
Indicates that an entity has a relationship to, or is characterized or categorized by, the size of a company (e.g., small, medium, large).
-
E.
typicalGroupSize
Indicates the usual or characteristic number of individuals that typically form a group in this context.
- 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_69f0ef85f62081909842b59fdf8717e1 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_6a02008fcf1c8190b5b6c285944c52e9 |
completed | May 11, 2026, 4:15 p.m. |
| PD | Predicate disambiguation | batch_6a01ffd3ba008190b6f026bd4e6b9a37 |
completed | May 11, 2026, 4:12 p.m. |
Created at: April 28, 2026, 6:28 p.m.