Triple
T9619748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sophie Mol |
E232309
|
entity |
| Predicate | storyLocation |
P9801
|
FINISHED |
| Object | Ayemenem |
E811312
|
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: Ayemenem | Statement: [Sophie Mol, storyLocation, Ayemenem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ayemenem Context triple: [Sophie Mol, storyLocation, Ayemenem]
-
A.
Ayemenem
chosen
Ayemenem is a small village in the Indian state of Kerala, best known as the primary setting of Arundhati Roy’s novel "The God of Small Things."
-
B.
Angamaly
Angamaly is a town in the Ernakulam district of Kerala, India, known as a major transportation hub and gateway to the nearby Cochin International Airport.
-
C.
Kakkanad
Kakkanad is a rapidly developing suburban region of Kochi in Kerala, India, known as an administrative hub and major IT and industrial center.
-
D.
Kayadhu
Kayadhu is a figure in Hindu mythology known as the wife of the demon king Hiranyakashipu and the mother of the devotee Prahlada.
-
E.
Panambi
Panambi is a city in southern Brazil known for its strong German-Brazilian cultural heritage and traditions.
- 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_69ca84867bb88190b4b57dd5a56d5691 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9ad295008190a4418d092576cb53 |
completed | April 1, 2026, 10:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1c3fd3a2c81909a19aafd70b3c150 |
completed | April 5, 2026, 2:07 a.m. |
Created at: March 30, 2026, 8:09 p.m.