Triple
T4632419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elena Ochoa Foster |
E101447
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Elena |
E86412
|
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: Elena | Statement: [Elena Ochoa Foster, givenName, Elena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elena Context triple: [Elena Ochoa Foster, givenName, Elena]
-
A.
Elena
chosen
Elena is a feminine given name of Greek origin, commonly used in many languages as a variant of Helen or Helena.
-
B.
Elena of Avalor
Elena of Avalor is an animated Disney television series following a brave Latina princess who rules the magical kingdom of Avalor.
-
C.
Elena Hood
Elena Hood is a suburban wife and mother in the 1970s whose emotional disconnection and personal turmoil reflect the broader social and familial breakdown depicted in the film "The Ice Storm."
-
D.
Natalya
Natalya is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and derived from the Latin name Natalia.
-
E.
Valeria
Valeria is the clever, sharp-tongued heroine of George Farquhar’s Restoration comedy "The Witty Fair One."
- 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_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a342ffc8190a911d0598ed230bb |
completed | March 20, 2026, 2:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfabeba3c8190b6515b99746f62a6 |
completed | March 21, 2026, 1:56 a.m. |
Created at: March 20, 2026, 1:13 p.m.