Triple
T16355973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marquis of Veere and Vlissingen |
E397179
|
entity |
| Predicate | linkedTo |
P37
|
FINISHED |
| Object | Veere |
E361425
|
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: Veere | Statement: [Marquis of Veere and Vlissingen, linkedTo, Veere]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Veere Context triple: [Marquis of Veere and Vlissingen, linkedTo, Veere]
-
A.
Veere
chosen
Veere is a historic harbor town and former trading center located on the island of Walcheren in the Dutch province of Zeeland.
-
B.
Vinai
Vinai is the given name of Vinai Kumar Saxena, an Indian administrator and public figure.
-
C.
Maninka
Maninka is a Mande language of West Africa, closely related to Mandinka and Bambara, and widely used as a lingua franca in Guinea and neighboring regions.
-
D.
Varalaru
Varalaru is a 2006 Tamil-language drama film starring Ajith Kumar in a celebrated triple role, noted for its emotional depth and commercial success.
-
E.
Vaini
Vaini is a coastal village and district on the southern side of Tongatapu in Tonga, known as one of the island’s main population centers.
- 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2face3a54819099418edd0eecc963 |
completed | April 18, 2026, 3:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002dbaacd88190b2c90c5be2832307 |
completed | May 10, 2026, 7:03 a.m. |
Created at: April 10, 2026, 5:07 a.m.