Triple
T6590140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greifswald |
E159331
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Harlow |
E163496
|
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: Harlow | Statement: [Greifswald, twinTown, Harlow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harlow Context triple: [Greifswald, twinTown, Harlow]
-
A.
Harlow
Harlow is a 1965 biographical drama film about the life and career of Hollywood actress Jean Harlow.
-
B.
Harlow
chosen
Harlow is a town in Essex, England, known as a post-war New Town with significant residential, commercial, and industrial development.
-
C.
Peabody
Peabody is a suburban city in northeastern Massachusetts known for its location on the North Shore and its historical ties to the leather industry.
-
D.
Haddon Heights
Haddon Heights is a small suburban borough in southern New Jersey known for its historic homes, tree-lined streets, and close-knit community.
-
E.
Orem
Orem is a city in northern Utah known for its family-friendly suburbs, proximity to Provo, and the presence of Utah Valley University.
- 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_69c688366ce8819083f8883983c0df92 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6aeb201e88190808cf5779349f96c |
completed | March 27, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d57bde388190919ff6820e1b9610 |
completed | March 27, 2026, 7:07 p.m. |
Created at: March 27, 2026, 1:55 p.m.