Triple
T9704709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nashik district |
E234869
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Manmad |
E546639
|
NE 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: Manmad | Statement: [Nashik district, containsTown, Manmad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Manmad Context triple: [Nashik district, containsTown, Manmad]
-
A.
Manmad
chosen
Manmad is a major railway and commercial town in Maharashtra, India, known as an important junction connecting several key routes in the region.
-
B.
Manmadhudu
Manmadhudu is a popular 2002 Telugu romantic comedy film starring Nagarjuna Akkineni, known for its witty humor and charming portrayal of a commitment-phobic ad executive.
-
C.
Muthaiga
Muthaiga is an affluent residential suburb of Nairobi, Kenya, known for its upscale homes, diplomatic residences, and exclusive social clubs.
-
D.
Manthara
Manthara is a pivotal character in the Indian epic Ramayana, known as Queen Kaikeyi’s scheming maid whose manipulation leads to Rama’s exile.
-
E.
Amanush
Amanush is a 1975 Bengali-Hindi thriller drama film, widely remembered for Uttam Kumar’s acclaimed performance and its exploration of betrayal and redemption in a rural setting.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca84cc78808190a56f3402b7c139a7 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9d74afb4819084174aab5bcdb6e0 |
completed | April 1, 2026, 10:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d19136b40c8190922052dd84d49f15 |
completed | April 4, 2026, 10:31 p.m. |
Created at: March 30, 2026, 8:18 p.m.