Triple
T7379109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Demophon |
E170201
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Acamas |
E174052
|
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: Acamas | Statement: [Demophon, sibling, Acamas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Acamas Context triple: [Demophon, sibling, Acamas]
-
A.
Acamas
chosen
Acamas is a figure in Greek mythology, traditionally known as a son of the Athenian hero Theseus who took part in events surrounding the Trojan War.
-
B.
Alpedrete
Alpedrete is a municipality in the Community of Madrid, Spain, known for its traditional stone quarries and residential character near the Sierra de Guadarrama.
-
C.
Tocopilla
Tocopilla is a coastal city and port in northern Chile known for its mining industry and location on the Pacific Ocean.
-
D.
Tezonco
Tezonco is a metro station in Mexico City that serves the southeastern area of the city on the capital’s rapid transit network.
-
E.
Tecuala
Tecuala is a municipality and town in the Mexican state of Nayarit, known for its agricultural activities and proximity to coastal wetlands along the Pacific.
- 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_69c68a5d0ed08190b6d361e68f813330 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f1c4ad0081909386fbef9f61ae4c |
completed | March 27, 2026, 9:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c802d86da48190a1311c5c52a5f296 |
completed | March 28, 2026, 4:33 p.m. |
Created at: March 27, 2026, 3:08 p.m.