Triple
T6555895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Simone |
E152444
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Simi |
E208020
|
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: Simi | Statement: [Simone, hasDiminutive, Simi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Simi Context triple: [Simone, hasDiminutive, Simi]
-
A.
Simi
chosen
Simi is a Greek island in the Dodecanese archipelago in the southeastern Aegean Sea, near the coast of Turkey.
-
B.
Simmi
Simmi is a low-lying locality or geographic feature in the Swiss municipality of Wildhaus, notable as its lowest elevation point.
-
C.
Shila Ommi
Shila Ommi is an Iranian-American actress known for her film, television, and voice roles, including work in major animated features.
-
D.
Alka
Alka is the first name of Alka Yagnik, a renowned Indian playback singer known for her extensive work in Bollywood music.
-
E.
Siwan
Siwan is a town and district headquarters in the Indian state of Bihar, known for its historical significance and political prominence.
- 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_69c688058d6881908c19b309cc55dbfa |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ae1d28bc8190a2fa4b3e1e39863c |
completed | March 27, 2026, 4:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d559ad4881909c1e7712d84945f6 |
completed | March 27, 2026, 7:07 p.m. |
Created at: March 27, 2026, 1:51 p.m.