Triple
T18472656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ponta do Sol |
E451339
|
entity |
| Predicate | nearbyTown |
P3883
|
FINISHED |
| Object | Paul |
—
|
NE NERFINISHED |
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: Paul | Statement: [Ponta do Sol, nearbyTown, Paul]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paul Context triple: [Ponta do Sol, nearbyTown, Paul]
-
A.
Paul
Paul is a character in the film "Her," known as Theodore Twombly’s supportive and easygoing close friend.
-
B.
Paul
Paul is a 2011 sci-fi comedy film about two British geeks who encounter a wisecracking alien during a road trip across the United States.
-
C.
Paul
chosen
Paul is a village and civil parish in Cornwall, England, known for its historic church and coastal setting near Penzance.
-
D.
Paul
Paul is a character in the crime drama film "Never Die Alone," which follows the violent, intertwined lives of drug dealers and those around them.
-
E.
Paul
Paul is a central character in the psychological horror film "It Comes at Night," portrayed as a protective family man struggling to safeguard his loved ones amid a mysterious, apocalyptic threat.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38465a0819099b9b42d2a662ac1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e530617e48819091240d4405e53aaa |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 11:34 a.m.