Triple
T20191522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marth |
E492988
|
entity |
| Predicate | homeLocation |
P75
|
FINISHED |
| Object | Altea |
—
|
NE NERFINISHED |
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: Altea | Statement: [Marth, homeLocation, Altea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Altea Context triple: [Marth, homeLocation, Altea]
-
A.
Altea
chosen
Altea is a picturesque coastal town on Spain’s Costa Blanca, known for its whitewashed old quarter, blue-domed church, and vibrant arts scene.
-
B.
Javea
Javea is a coastal town on Spain’s Costa Blanca known for its Mediterranean beaches, historic old town, and popular holiday tourism.
-
C.
Denia
Denia is a coastal city on Spain’s Costa Blanca known for its historic castle, Mediterranean beaches, and vibrant port.
-
D.
Alcúdia
Alcúdia is a historic coastal town in northern Mallorca, Spain, known for its well-preserved medieval walls, charming old town, and nearby sandy beaches.
-
E.
Alcoy
Alcoy is an industrial and historically significant city in southeastern Spain, known for its textile heritage, modernist architecture, and famous Moors and Christians festival.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad593f88190a1e534fed38b3cd7 |
completed | April 20, 2026, 6:05 p.m. |
Created at: April 11, 2026, 11:37 p.m.