Triple
T26561627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terschelling |
E666257
|
entity |
| Predicate | hasOldestDutchLighthouse |
P61255
|
FINISHED |
| Object | Brandaris |
—
|
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: Brandaris | Statement: [Terschelling, hasOldestDutchLighthouse, Brandaris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOldestDutchLighthouse Context triple: [Terschelling, hasOldestDutchLighthouse, Brandaris]
-
A.
isOldestLighthouseOn
chosen
Indicates that one lighthouse is the oldest existing lighthouse located on a specified landmass or geographic area.
-
B.
isOldestContinuouslyOperatingLighthouseIn
Indicates that a lighthouse is the oldest one in a given place that has remained in continuous operation without interruption.
-
C.
hasFormerZuiderzeeTown
Indicates that a place has, within its boundaries or jurisdiction, a town that historically lay on the shores of the former Zuiderzee.
-
D.
hasOldestIsland
Indicates that one entity possesses or is associated with the island that is the oldest among a specified set or group.
-
E.
isOldestMuseumIn
Indicates that a museum is the most ancient or earliest established museum within a specified location or region.
- F. None of above.
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_69ee9cf7e94481909f0d556b36e43572 |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f61a17a7788190946f7e32d63cd43f |
completed | May 2, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69f611ab768c8190b1849c15a3e59dda |
completed | May 2, 2026, 3 p.m. |
Created at: April 27, 2026, 1:53 a.m.