Triple
T13216775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aegiali |
E314635
|
entity |
| Predicate | hasNearbySettlement |
P4647
|
FINISHED |
| Object | Lagada |
E314637
|
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: Lagada | Statement: [Aegiali, hasNearbySettlement, Lagada]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lagada Context triple: [Aegiali, hasNearbySettlement, Lagada]
-
A.
Lagada
chosen
Lagada is a small traditional village on the Greek island of Amorgos, known for its whitewashed houses, hillside setting, and views over the Aegean Sea.
-
B.
Lagunna
Lagunna is a titled chief within the Oyo Mesi, the council of kingmakers and principal nobles in the traditional Oyo Yoruba political system.
-
C.
Laja
Laja is a small Chilean city in the Biobío Region, known for its riverside setting and proximity to the Biobío River.
-
D.
Lagar
Lagar is a poetry collection by Chilean Nobel laureate Gabriela Mistral that reflects her mature, introspective, and often somber lyrical style.
-
E.
Barbalha
Barbalha is a municipality in northeastern Brazil known for its traditional cultural festivals and location in the state of Ceará.
- 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_69d806aee7308190b70a237ba2a6e3e1 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf28c9c819080d7b42d20f579d1 |
completed | April 10, 2026, 11:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff1ebf648190a27d11b3dc494446 |
completed | May 3, 2026, 7:54 a.m. |
Created at: April 9, 2026, 9:18 p.m.