Triple
T11860462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SITE Town |
E282143
|
entity |
| Predicate | industrialEstateRankInPakistan |
P101900
|
FINISHED |
| Object | one of the largest industrial estates in Pakistan |
—
|
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: one of the largest industrial estates in Pakistan | Statement: [SITE Town, industrialEstateRankInPakistan, one of the largest industrial estates in Pakistan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: industrialEstateRankInPakistan Context triple: [SITE Town, industrialEstateRankInPakistan, one of the largest industrial estates in Pakistan]
-
A.
areaRankInPakistan
Indicates the relative position of an entity when all entities in Pakistan are ordered by their area size.
-
B.
hasIndustrialParkName
Indicates that an entity (such as an industrial park or related facility) bears or is identified by a specific industrial park name.
-
C.
hasIndustrialPark
Indicates that a location or entity possesses or contains an industrial park within its area or jurisdiction.
-
D.
populationRankInSindh
Indicates the relative position of an entity in terms of population size compared to other entities within Sindh.
-
E.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a69a099c8190a674db64c50eca5a |
completed | April 10, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69d8a2573dbc8190ab432e8e28fde6cc |
completed | April 10, 2026, 7:10 a.m. |
| PDg | Predicate description generation | batch_69d8a43cc0c881909fed7cd759fe90b1 |
completed | April 10, 2026, 7:18 a.m. |
Created at: April 8, 2026, 9:43 p.m.