Triple
T33496937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tram line 4 (Budapest) |
E857886
|
entity |
| Predicate | sharesRouteSectionWith |
P41108
|
FINISHED |
| Object | Tram line 6 (Budapest) |
—
|
NE NERFINISHED |
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: Tram line 6 (Budapest) | Statement: [Tram line 4 (Budapest), sharesRouteSectionWith, Tram line 6 (Budapest)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesRouteSectionWith Context triple: [Tram line 4 (Budapest), sharesRouteSectionWith, Tram line 6 (Budapest)]
-
A.
sharesRouteWith
Indicates that two entities follow or operate along the same or overlapping route.
-
B.
sharesSectionsWith
chosen
Indicates that two entities have one or more sections or segments in common.
-
C.
sharesModuleWith
Indicates that two entities are associated with or participate in at least one common module.
-
D.
sharesUniverseWith
Indicates that two entities exist within the same fictional or narrative universe, implying shared continuity, setting, or canon.
-
E.
sharesContextWith
Indicates that two entities occur within or are associated with the same situational, semantic, or environmental context.
- 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_69f3497660508190a541826a81f7e9ab |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ffacdf9f5c8190baef0245edfe87fc |
completed | May 9, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69ffac5e86e08190a1e6da0840a237ad |
completed | May 9, 2026, 9:51 p.m. |
Created at: May 1, 2026, 1:38 a.m.