Triple
T1941955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metro L Line (Los Angeles) |
E41573
|
entity |
| Predicate | hasPlannedChange |
P22587
|
FINISHED |
| Object | integration into restructured Metro Rail network |
—
|
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: integration into restructured Metro Rail network | Statement: [Metro L Line (Los Angeles), hasPlannedChange, integration into restructured Metro Rail network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlannedChange Context triple: [Metro L Line (Los Angeles), hasPlannedChange, integration into restructured Metro Rail network]
-
A.
hasPlanningStatus
Indicates that an entity is associated with a particular stage, condition, or outcome in a planning or approval process.
-
B.
hasPlan
Indicates that an entity possesses or is associated with a specific plan or course of action.
-
C.
hasPlanningCharacteristic
Indicates that an entity possesses a specific feature, quality, or attribute related to planning activities or processes.
-
D.
hasPlannedInstitution
Indicates that an entity has an associated institution that is intended or scheduled to be established or implemented in the future.
-
E.
hasResultingChange
chosen
Indicates that one entity causes or leads to a specific change or transformation in another entity or state.
- 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_69a88649b24c819080047f26b6db2ded |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abaff25a588190bb4cbc8df9fc6d64 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.