Triple
T37300925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Houston–Dallas |
E925937
|
entity |
| Predicate | hasApproximateLength_mi |
P26813
|
FINISHED |
| Object | 240 |
—
|
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: 240 | Statement: [Houston–Dallas, hasApproximateLength_mi, 240]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateLength_mi Context triple: [Houston–Dallas, hasApproximateLength_mi, 240]
-
A.
approximateLengthInMeters
Indicates the estimated or roughly measured length of something expressed in meters.
-
B.
hasApproximateLengthCategory
Indicates that one entity is classified into a broad or approximate category based on its length.
-
C.
approximateLengthInMiles
chosen
Indicates the estimated distance or extent of something measured in miles.
-
D.
longitudAproximada
Indicates an approximate measurement of the length of something, rather than its exact value.
-
E.
hasApproximateLengthInState
Indicates that an entity’s length, measured under a specified condition or state, is approximately equal to a given value.
- 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_69f76eb1bc508190924e9fa5d8acdeb3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fe72dca2f08190beff17de3d2aada6 |
completed | May 8, 2026, 11:33 p.m. |
| PD | Predicate disambiguation | batch_69fe70bca8d08190b810e1e616ceac44 |
completed | May 8, 2026, 11:24 p.m. |
Created at: May 3, 2026, 4:16 p.m.