Triple
T4574630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denguin |
E123113
|
entity |
| Predicate | hasAdministrativeCentre |
P1474
|
FINISHED |
| Object | Denguin |
E123113
|
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: Denguin | Statement: [Denguin, hasAdministrativeCentre, Denguin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Denguin Context triple: [Denguin, hasAdministrativeCentre, Denguin]
-
A.
Denguin
chosen
Denguin is a small commune in southwestern France, located in the Pyrénées-Atlantiques department in the Nouvelle-Aquitaine region.
-
B.
Daggoo
Daggoo is a powerful African harpooner aboard the whaling ship Pequod in Herman Melville’s novel "Moby-Dick."
-
C.
Dug
Dug is the lovable, talking golden retriever from Pixar's animated film "Up," known for his collar that translates his thoughts into speech and his enthusiastic, friendly personality.
-
D.
Doo-Dah
Doo-Dah is a quirky, affectionate nickname used by locals to refer to the city of Wichita, Kansas.
-
E.
Phander
Phander is a picturesque village in northern Pakistan’s Gilgit-Baltistan region, known for its turquoise river, lush valley landscape, and proximity to the scenic Phander Lake.
- 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_69bd46466c7081909d07f36be2d08804 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd58c9f0bc81908d87f01ab067818a |
completed | March 20, 2026, 2:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdd3dde41c81909adf91b53450e590 |
completed | March 20, 2026, 11:10 p.m. |
Created at: March 20, 2026, 1:10 p.m.