Triple
T16238043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quentin |
E394165
|
entity |
| Predicate | shortForm |
P43
|
FINISHED |
| Object | Quin |
E301097
|
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: Quin | Statement: [Quentin, shortForm, Quin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Quin Context triple: [Quentin, shortForm, Quin]
-
A.
Quin
chosen
Quin is a given name, often used as a variant of Quinn, that can function as a unisex first name or surname.
-
B.
Quin
Quin is a historic village in County Clare, Ireland, known for the ruins of Quin Abbey and its picturesque rural setting.
-
C.
Oquin
Oquin is a family surname closely related to the surname O'Quinn, likely sharing similar origins and lineage.
-
D.
Anda
Anda is a coastal island municipality in the Philippine province of Pangasinan known for its beaches and fishing communities.
-
E.
Anda
Anda is a coastal municipality on the eastern tip of Bohol Island in the Philippines, known for its white-sand beaches, caves, and relatively undeveloped, laid-back atmosphere.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2455c7a3c81909e3b42edf03be43e |
completed | April 17, 2026, 2:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000edaf76c8190acc01f58845e570a |
completed | May 10, 2026, 4:51 a.m. |
Created at: April 10, 2026, 5:04 a.m.