Triple
T26049861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howrah–Kharagpur railway line |
E647939
|
entity |
| Predicate | servesIndustrialArea |
P74434
|
FINISHED |
| Object | Haldia region (via Panskura) |
—
|
NE NERFINISHED |
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: Haldia region (via Panskura) | Statement: [Howrah–Kharagpur railway line, servesIndustrialArea, Haldia region (via Panskura)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesIndustrialArea Context triple: [Howrah–Kharagpur railway line, servesIndustrialArea, Haldia region (via Panskura)]
-
A.
servesIndustrialRegion
chosen
Indicates that an entity provides services or support to an industrial region, fulfilling functional or operational needs of that area.
-
B.
isIndustrialAreaOf
Indicates that a location functions primarily as an industrial zone or district associated with a specified area or jurisdiction.
-
C.
servesIndustrialCity
Indicates that something functions to provide services, support, or utility to an industrial city.
-
D.
hasIndustrialAreaType
Indicates that an entity’s industrial area is classified as a specific type or category of industrial zone.
-
E.
connectsToIndustrialArea
Indicates that one entity has a direct link, route, or access connection to an industrial area.
- 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_69e77e8d419481908004e6318d28aaab |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f7221dc9a88190bb8194fcc29c42bc |
completed | May 3, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
Created at: April 22, 2026, 9:10 a.m.