Triple
T3089552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suffolk |
E64456
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Eye |
E266376
|
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: Eye | Statement: [Suffolk, containsSettlement, Eye]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eye Context triple: [Suffolk, containsSettlement, Eye]
-
A.
Eye
chosen
Eye is a small historic market town in Suffolk, England, known for its medieval architecture and rural surroundings.
-
B.
Göz-Göz
Göz-Göz is the popular nickname of Turkish football club Göztepe S.K., widely used by its passionate fanbase and in Turkish sports culture.
-
C.
Lens
Lens is a commune in northern France known for its mining heritage and the Louvre-Lens art museum.
-
D.
Eye to Eye
Eye to Eye is a creative work whose title matches its own name, likely a book, film, song, or television program centered on themes of direct confrontation or mutual understanding.
-
E.
Ayin
Ayin is the sixteenth letter of the Hebrew alphabet, traditionally representing a voiced pharyngeal fricative and often functioning as a silent consonant in modern Hebrew.
- 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_69ad857c97d88190b26f9b1c90839c77 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada20d8f788190b05b8b6b5042bc1a |
completed | March 8, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1f8a4c1f08190a80efd190e4ed07f |
completed | March 11, 2026, 11:20 p.m. |
Created at: March 8, 2026, 3:03 p.m.