Triple
T7180254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cape Agulhas |
E167427
|
entity |
| Predicate | lighthouseColor |
P75864
|
FINISHED |
| Object | white and red bands |
—
|
LITERAL 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: white and red bands | Statement: [Cape Agulhas, lighthouseColor, white and red bands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lighthouseColor Context triple: [Cape Agulhas, lighthouseColor, white and red bands]
-
A.
lanternColor
Indicates that one entity specifies or describes the color attribute of a lantern associated with another entity.
-
B.
lighthouseStatus
Indicates the operational condition or state (e.g., active, inactive, under maintenance) of a lighthouse at a given time.
-
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.
lighthouseConstructedIn
Indicates that a lighthouse was built or established during a specific time period or in a specific year.
- F. None of above. chosen
Provenance (4 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_69c6888a7c548190a3d39b52a393080f |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e9b045c48190b27b2d6f7c11026f |
completed | March 27, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69c6e74fb0f48190b2ad4dd4efdd241a |
completed | March 27, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69c6e9aeb1b08190ace6f978387c89aa |
completed | March 27, 2026, 8:33 p.m. |
Created at: March 27, 2026, 2:49 p.m.