Triple
T25448147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lamb Pass |
E637695
|
entity |
| Predicate | hasHairpinCount |
P17038
|
FINISHED |
| Object | numerous hairpin turns |
—
|
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: numerous hairpin turns | Statement: [Lamb Pass, hasHairpinCount, numerous hairpin turns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHairpinCount Context triple: [Lamb Pass, hasHairpinCount, numerous hairpin turns]
-
A.
hasNumberOfHairpinTurns
chosen
Indicates the quantity of hairpin turns associated with an entity, such as a road or path.
-
B.
hasHairpinBends
Indicates that a route, road, or path includes very sharp, U-shaped turns resembling hairpins.
-
C.
hairpinsNumberedFrom
Indicates that a set of hairpins is assigned distinct identifiers or positions according to a specific numbering scheme.
-
D.
hasPinCount
Indicates that an entity is associated with a specific number of pins.
-
E.
hasNumberOfPins
Indicates that an entity is associated with a specific count of pins it possesses or uses.
- 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_69e75db7c5048190b8da9cd7eeedb610 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f70518e48190ae918ff33e342c82 |
completed | May 2, 2026, 1:07 p.m. |
| PD | Predicate disambiguation | batch_69f4806d93dc8190b9dff4c63186faff |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 2:02 p.m.