Triple
T7610730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mercedes Barcha |
E172227
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Barcha |
E172227
|
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: Barcha | Statement: [Mercedes Barcha, familyName, Barcha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barcha Context triple: [Mercedes Barcha, familyName, Barcha]
-
A.
Barcha
chosen
Barcha is the surname of Mercedes Barcha, the Colombian wife and lifelong companion of Nobel Prize–winning author Gabriel García Márquez.
-
B.
Baar
Baar is a municipality in the canton of Zug in central Switzerland, known for its favorable tax environment and mix of residential areas and international businesses.
-
C.
Tous
Tous is a Spanish jewelry and accessories brand known for its distinctive teddy bear logo and affordable luxury designs.
-
D.
Baran
Baran is a city in the Hadoti region of Rajasthan, India, known for its historical temples, forts, and proximity to natural attractions like waterfalls and wildlife sanctuaries.
-
E.
Baran
Baran is a surname most notably associated with Paul Baran, a pioneering engineer of packet-switched networks and early internet technology.
- 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_69c6994f50808190ba228764bb422417 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fa20ac2c8190ac7ab90b4df406b6 |
completed | March 27, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c868600c7c81909cdeebdb5b2bdaf3 |
completed | March 28, 2026, 11:46 p.m. |
Created at: March 27, 2026, 3:54 p.m.