Triple
T9172179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eravikulam National Park |
E220105
|
entity |
| Predicate | distanceFromMunnar |
P86631
|
FINISHED |
| Object | about 13 kilometres |
—
|
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: about 13 kilometres | Statement: [Eravikulam National Park, distanceFromMunnar, about 13 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMunnar Context triple: [Eravikulam National Park, distanceFromMunnar, about 13 kilometres]
-
A.
distanceFromShillong
Indicates the spatial distance between a given entity or location and Shillong.
-
B.
distanceToSrinagar_km
Indicates the physical distance, measured in kilometers, between a given place or entity and the city of Srinagar.
-
C.
distanceFromShimla_km
Indicates the physical distance, measured in kilometers, between a given place and Shimla.
-
D.
distanceToDharamshala
Indicates the spatial distance between a given entity and the location of Dharamshala.
-
E.
distanceFromAngamaly_km
Indicates the distance, measured in kilometers, between a given place and Angamaly.
- 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_69ca83e467108190abcae6a33b3d4dad |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccbf9fe79c819082f335c2fdd1c7d3 |
completed | April 1, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69cc660761d88190ab6134b43b376964 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc66d7bf648190b8bff5b584b84975 |
completed | April 1, 2026, 12:29 a.m. |
Created at: March 30, 2026, 7:22 p.m.