Triple
T9896093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bajawa |
E182175
|
entity |
| Predicate | isOnIsland |
P3864
|
FINISHED |
| Object | Flores |
E29474
|
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: Flores | Statement: [Bajawa, isOnIsland, Flores]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Flores Context triple: [Bajawa, isOnIsland, Flores]
-
A.
Flores
Flores is a Spanish-origin surname common in the Hispanic world and borne by numerous notable figures in sports, politics, and the arts.
-
B.
Flores
chosen
Flores is a large island in eastern Indonesia known for its volcanic landscapes, traditional villages, and proximity to Komodo National Park with its famous Komodo dragons.
-
C.
Flores
Flores is a historic island city in northern Guatemala known for its colonial architecture and as a gateway to the nearby Maya ruins of Tikal.
-
D.
Flores
Flores is a traditional residential neighborhood in the western part of Buenos Aires, Argentina, known for its historic churches, busy commercial avenues, and role as a major middle-class district of the city.
-
E.
Flores Island
Flores Island is a remote, lushly vegetated island in the western Azores archipelago of Portugal, known for its dramatic cliffs, waterfalls, and crater lakes.
- 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_69ca82876f8081909cf75df0f99bb13f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb4a9d2f4819086cfdd42b613cd8c |
completed | April 2, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d299c51ea08190902e03552fbe7ebb |
completed | April 5, 2026, 5:20 p.m. |
Created at: March 30, 2026, 8:39 p.m.