Triple
T20530778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Los Angeles–San Francisco |
E504060
|
entity |
| Predicate | hasMajorMode |
P140444
|
FINISHED |
| Object | rail |
—
|
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: rail | Statement: [Los Angeles–San Francisco, hasMajorMode, rail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorMode Context triple: [Los Angeles–San Francisco, hasMajorMode, rail]
-
A.
hasMajorType
Indicates that an entity belongs to or is categorized under a primary or overarching type or classification.
-
B.
hasMajorComponent
Indicates that one entity includes another entity as a primary or most significant component or part.
-
C.
hasMajor
Indicates that an entity (typically a person or student) has a specific primary field of academic study or specialization.
-
D.
hasMajorCategory
Indicates that something is associated with or classified under a primary, overarching category.
-
E.
hasMajorRange
Indicates that one entity encompasses or defines the primary or most extensive range or scope associated with another entity.
- 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_69e0b4b3a6e08190ae663701f50fab8e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a06b923c81908ba24be6645a7c61 |
completed | April 20, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69e59fdb7ad88190924176c32a195db3 |
completed | April 20, 2026, 3:39 a.m. |
| PDg | Predicate description generation | batch_69e5a6a824748190bbe6192d73f3c613 |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:37 a.m.