Triple
T14561589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alstom Eurotram |
E341678
|
entity |
| Predicate | hasTypicalConfiguration |
P67991
|
FINISHED |
| Object | 7-section articulated tram |
—
|
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: 7-section articulated tram | Statement: [Alstom Eurotram, hasTypicalConfiguration, 7-section articulated tram]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalConfiguration Context triple: [Alstom Eurotram, hasTypicalConfiguration, 7-section articulated tram]
-
A.
hasConfiguration
Indicates that an entity is associated with or defined by a particular configuration or setup.
-
B.
hasTypicalPlan
Indicates that there is a standard or commonly followed plan, procedure, or course of action typically associated with the given entity or situation.
-
C.
typicalUnitConfiguration
chosen
Indicates the standard or commonly used arrangement, composition, or setup of a unit in a given context.
-
D.
hasTypicalAccess
Indicates that one entity normally or customarily has the ability, permission, or means to access or use another entity.
-
E.
hasTypicalCharacterType
Indicates that an entity is commonly associated with or exemplified by a particular type of character or persona.
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb389d0f48190a1d9d69456d1cbe1 |
completed | April 14, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69de5c57489c8190b57917be1dba6ae6 |
completed | April 14, 2026, 3:25 p.m. |
Created at: April 10, 2026, 1:23 a.m.