Triple
T222443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Tráfico |
E4244
|
entity |
| Predicate | nameAlludesTo |
P4929
|
FINISHED |
| Object | Los Angeles traffic congestion |
—
|
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: Los Angeles traffic congestion | Statement: [El Tráfico, nameAlludesTo, Los Angeles traffic congestion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameAlludesTo Context triple: [El Tráfico, nameAlludesTo, Los Angeles traffic congestion]
-
A.
titleAlludesTo
chosen
Indicates that one title makes an indirect or suggestive reference to the content, theme, or another work associated with the other.
-
B.
nameGivesRiseTo
Indicates that one name, term, or designation leads to, causes, or results in the emergence or establishment of another.
-
C.
nameOf
Indicates that one entity is the name or designation of another entity.
-
D.
alsoKnownAs
Indicates that one entity is an alternative name, alias, or designation for another entity.
-
E.
hasFamousNamesakeRole
Indicates that an entity has a role or position that shares its name with a well-known or historically notable person.
- 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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c705fd88190bfee7f5e1f7cee17 |
completed | Feb. 28, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69a25b5617788190814358aee3f7ae37 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.