Triple
T16576068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Celaque massif |
E402711
|
entity |
| Predicate | nearestTown |
P350
|
FINISHED |
| Object | Gracias |
E402712
|
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: Gracias | Statement: [Celaque massif, nearestTown, Gracias]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gracias Context triple: [Celaque massif, nearestTown, Gracias]
-
A.
Gracias
chosen
Gracias is a historic colonial town in western Honduras known for its preserved architecture and proximity to the Celaque National Park and Cerro Las Minas.
-
B.
Grazie
Grazie is a 2006 studio album by Italian rock singer-songwriter Gianna Nannini that blends pop-rock sounds with introspective, socially aware lyrics.
-
C.
Graças
Graças is a traditional, upscale residential neighborhood in the city of Recife, Brazil, known for its tree-lined streets, historic houses, and proximity to the city center.
-
D.
Thank U
"Thank U" is a reflective alternative rock song by Alanis Morissette, known for its introspective lyrics about gratitude and personal growth.
-
E.
Thanks
"Thanks" is a film featuring Erika Christensen in a notable role.
- 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_69d88387363c8190a97a0c942130de97 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3595cb65481909be62a52deff3d44 |
completed | April 18, 2026, 10:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007595cfd08190bae54d29427a1d3c |
completed | May 10, 2026, 12:09 p.m. |
Created at: April 10, 2026, 5:16 a.m.