Triple
T16109566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gil Samaniego |
E390837
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | Gil |
E413170
|
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: Gil | Statement: [Gil Samaniego, hasComponent, Gil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gil Context triple: [Gil Samaniego, hasComponent, Gil]
-
A.
Gil
chosen
Gil is a common shortened form of the given name Gilbert, used as a familiar or informal variant.
-
B.
Gil
Gil is a common Spanish surname borne by numerous individuals across various fields, including sports, arts, and public life.
-
C.
Guil
The Guil is a mountain river in southeastern France that flows through the Queyras region of the Alps before joining the Durance.
-
D.
Gilillo
Gilillo is the highest peak in Spain’s Sierra de Cazorla mountain range, known for its scenic hiking routes and panoramic views.
-
E.
Gib
Gib is a supporting character in the action-comedy film "True Lies," serving as Harry Tasker's tech-savvy and wisecracking partner in the secret government agency.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2016665c0819081aa7a44b1d08183 |
completed | April 17, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeba674788190a589104cf90f28d5 |
completed | May 10, 2026, 2:21 a.m. |
Created at: April 10, 2026, 5 a.m.