Triple
T7217807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Textile City |
E150179
|
entity |
| Predicate | linkedSector |
P75504
|
FINISHED |
| Object | garment manufacturing |
—
|
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: garment manufacturing | Statement: [Textile City, linkedSector, garment manufacturing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedSector Context triple: [Textile City, linkedSector, garment manufacturing]
-
A.
linkedLocation
Indicates that one location is associated or connected to another location in a meaningful way, such as being related, referenced, or contextually tied.
-
B.
linkedByStructure
Indicates that two entities are connected or associated through a shared structural element, configuration, or framework.
-
C.
linkedToRegion
Indicates that one entity is associated or connected to a specific geographic or administrative region.
-
D.
linkedPosition
Indicates that one position is associated or connected to another position in a defined way.
-
E.
tracksSector
Indicates that one entity monitors, follows, or keeps records of the status or performance of a particular sector.
- F. None of above. chosen
Provenance (4 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_69c687effb44819092b95d07d0368c9f |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e99170d88190b1aef326a7d81134 |
completed | March 27, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69c6e75f84e481909e7866186ae80cff |
completed | March 27, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69c6e889854481908c765ce2107f2d3a |
completed | March 27, 2026, 8:28 p.m. |
Created at: March 27, 2026, 2:53 p.m.