Triple
T26657988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | camelback hills |
E666562
|
entity |
| Predicate | heightRelation |
P161096
|
FINISHED |
| Object | can be uniform in height |
—
|
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: can be uniform in height | Statement: [camelback hills, heightRelation, can be uniform in height]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heightRelation Context triple: [camelback hills, heightRelation, can be uniform in height]
-
A.
heightRelation
Indicates a comparative relationship between entities based on their heights, such as one being taller, shorter, or the same height as another.
-
B.
heightReference
Indicates that one entity’s height is being measured, compared, or defined relative to another specified reference point or standard.
-
C.
heightContext
Indicates a contextual or situational relationship that specifies how an entity’s height is defined, measured, or interpreted in a particular setting or frame of reference.
-
D.
heightOptions
Indicates the available or specified height choices associated with an entity or configuration.
-
E.
heightClass
Indicates the categorical height level or range to which an entity is assigned (e.g., short, medium, tall).
- 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_69ee9cf8c7188190b9b00270a8a89164 |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f61ad613608190855de13501a86007 |
completed | May 2, 2026, 3:40 p.m. |
| PD | Predicate disambiguation | batch_69f611ab768c8190b1849c15a3e59dda |
completed | May 2, 2026, 3 p.m. |
| PDg | Predicate description generation | batch_69f61a16b7848190bf20d2be7e5a16c1 |
completed | May 2, 2026, 3:36 p.m. |
Created at: April 27, 2026, 2:35 a.m.