Triple
T14271735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Navsari district |
E353802
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Chikhli
Chikhli is a town in the Navsari district of Gujarat, India, known as a local commercial and transportation hub for surrounding rural areas.
|
E1100154
|
NE FINISHED |
How this triple was built (4 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: Chikhli | Statement: [Navsari district, hasTown, Chikhli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chikhli Context triple: [Navsari district, hasTown, Chikhli]
-
A.
Chikhli
Chikhli is a town in the Buldhana district of Maharashtra, India, known as a local commercial and administrative center for the surrounding rural region.
-
B.
Jwalapur
Jwalapur is a prominent suburban town and commercial hub near Haridwar in the Indian state of Uttarakhand.
-
C.
Chiplun
Chiplun is a town in Maharashtra, India, situated along the Vashishti River and known as a commercial and transport hub in the Konkan region.
-
D.
Lakdikapul
Lakdikapul is a prominent commercial and transit locality in central Hyderabad, known for its busy roads, hotels, and connectivity to major city hubs.
-
E.
Khandala
Khandala is a popular hill station in Maharashtra, India, known for its scenic valleys, waterfalls, and trekking spots in the Western Ghats.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Chikhli Triple: [Navsari district, hasTown, Chikhli]
Generated description
Chikhli is a town in the Navsari district of Gujarat, India, known as a local commercial and transportation hub for surrounding rural areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chikhli Target entity description: Chikhli is a town in the Navsari district of Gujarat, India, known as a local commercial and transportation hub for surrounding rural areas.
-
A.
Chikhli
Chikhli is a town in the Buldhana district of Maharashtra, India, known as a local commercial and administrative center for the surrounding rural region.
-
B.
Jwalapur
Jwalapur is a prominent suburban town and commercial hub near Haridwar in the Indian state of Uttarakhand.
-
C.
Chiplun
Chiplun is a town in Maharashtra, India, situated along the Vashishti River and known as a commercial and transport hub in the Konkan region.
-
D.
Lakdikapul
Lakdikapul is a prominent commercial and transit locality in central Hyderabad, known for its busy roads, hotels, and connectivity to major city hubs.
-
E.
Khandala
Khandala is a popular hill station in Maharashtra, India, known for its scenic valleys, waterfalls, and trekking spots in the Western Ghats.
- F. None of above. chosen
Provenance (5 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de65811d7c8190b075909a6570d415 |
completed | April 14, 2026, 4:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd647b37a8819095fe0bb62e0373fb |
completed | May 8, 2026, 4:20 a.m. |
| NEDg | Description generation | batch_69fd6539793881909d1fd3985c171837 |
completed | May 8, 2026, 4:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd65c06fc88190a7d2a84d7858b20f |
completed | May 8, 2026, 4:25 a.m. |
Created at: April 10, 2026, 1:10 a.m.