Triple
T2566692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asuncion |
E57366
|
entity |
| Predicate | nearbyIsland |
P2064
|
FINISHED |
| Object | Agrihan |
E54698
|
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: Agrihan | Statement: [Asuncion, nearbyIsland, Agrihan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Agrihan Context triple: [Asuncion, nearbyIsland, Agrihan]
-
A.
Agrihan
chosen
Agrihan is a remote volcanic island in the Northern Mariana Islands known for its large stratovolcano and rugged, sparsely populated landscape.
-
B.
Agrotera
Agrotera is an epithet of the Greek goddess Artemis that emphasizes her role as a huntress and protector of wild animals.
-
C.
Ghunsa
Ghunsa is a remote Himalayan village in eastern Nepal that serves as a key gateway and base for treks and expeditions around the Kangchenjunga region.
-
D.
Swadaya
Swadaya is a modern vernacular form of Neo-Aramaic traditionally written in the East Syriac script and used by Assyrian Christian communities.
-
E.
Landhi
Landhi is a major residential and industrial neighborhood in Karachi, Pakistan, known for its dense population and manufacturing zones.
- 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_69ab4a4ef9008190a0e6d4422b9418b7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3602ed08190aad0f9c7ac577eb0 |
completed | March 7, 2026, 7:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af6565e05081909dc12aa3240de5f2 |
completed | March 10, 2026, 12:27 a.m. |
Created at: March 6, 2026, 9:48 p.m.