Triple
T8024795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Timanfaya National Park |
E186825
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Timanfaya |
E195940
|
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: Timanfaya | Statement: [Timanfaya National Park, namedAfter, Timanfaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Timanfaya Context triple: [Timanfaya National Park, namedAfter, Timanfaya]
-
A.
Timanfaya
chosen
Timanfaya is a dramatic volcanic landscape and national park on the Spanish island of Lanzarote, renowned for its otherworldly lava fields and geothermal activity.
-
B.
Timaná
Timaná is a municipality and town in southern Colombia known for its colonial heritage and agricultural economy within the Andean region.
-
C.
Tashtego
Tashtego is a Native American harpooner from Herman Melville’s novel "Moby-Dick," serving aboard the whaling ship Pequod.
-
D.
Tannay
Tannay is a small lakeside municipality in the canton of Vaud in western Switzerland, situated on the shores of Lake Geneva.
-
E.
Timka
Timka is a Russian diminutive form of the male given name Timofey, typically used as an affectionate nickname.
- 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_69ca82ad4e2c8190a693e3c9e30fe66f |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3e90c7348190abc1013a312e4f1a |
completed | March 31, 2026, 3:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc56d41ec08190a19cb28e2e4b5bfe |
completed | March 31, 2026, 11:20 p.m. |
Created at: March 30, 2026, 5:21 p.m.