Triple
T26047966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cape of Needles |
E647884
|
entity |
| Predicate | lighthouseLocatedIn |
P140075
|
FINISHED |
| Object | Agulhas National Park |
—
|
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: Agulhas National Park | Statement: [Cape of Needles, lighthouseLocatedIn, Agulhas National Park]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lighthouseLocatedIn Context triple: [Cape of Needles, lighthouseLocatedIn, Agulhas National Park]
-
A.
lighthouseLocatedAt
chosen
Indicates that a lighthouse is situated at or associated with a specific geographic location.
-
B.
lighthouseConstructedIn
Indicates that a lighthouse was built or established during a specific time period or in a specific year.
-
C.
lighthouseHeight
Indicates the vertical measurement of a lighthouse from its base to its top.
-
D.
lighthouseName
Indicates that a lighthouse is identified by a specific name.
-
E.
lighthouseType
Indicates the specific classification or category of a lighthouse based on its design, function, or operational characteristics.
- 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_69e77e8d419481908004e6318d28aaab |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6065c200881908080a1069c63207b |
completed | May 2, 2026, 2:12 p.m. |
| PD | Predicate disambiguation | batch_69f5aff889988190ad10bcf1a280f717 |
completed | May 2, 2026, 8:04 a.m. |
Created at: April 22, 2026, 9:10 a.m.