Triple
T35269978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NH44 |
E1018637
|
entity |
| Predicate | connectsMajorRegions |
P200327
|
FINISHED |
| Object | Jammu and Kashmir |
—
|
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: Jammu and Kashmir | Statement: [NH44, connectsMajorRegions, Jammu and Kashmir]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsMajorRegions Context triple: [NH44, connectsMajorRegions, Jammu and Kashmir]
-
A.
connectsRegions
Indicates a relationship where one entity links or joins two or more distinct regions, enabling passage, interaction, or continuity between them.
-
B.
connectsMajorCity
Indicates that one entity serves as a link or route providing direct connection to a major city.
-
C.
connectsMetroAreas
Indicates a relationship where a transportation route or service links two or more metropolitan areas, enabling direct travel or interaction between them.
-
D.
connectsRemoteAreaToMajorCity
Indicates a relationship where a route, service, or infrastructure links a remote or rural area directly to a major city.
-
E.
connectsRegionalCity
Indicates a relationship where one entity serves as a link or transport route between a regional city and another location.
- 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_69f76de5c4788190896ad598ae7d6bc6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff80d9a1d88190a95b1488acd6e2e5 |
completed | May 9, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69ff802ae2dc819093a3cda42b63dcbd |
completed | May 9, 2026, 6:42 p.m. |
| PDg | Predicate description generation | batch_69ff80d8ff208190b9e95d077fd99f78 |
completed | May 9, 2026, 6:45 p.m. |
Created at: May 3, 2026, 4:02 p.m.