Triple
T18615051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lundie |
E454997
|
entity |
| Predicate | hasTransportCharacter |
P132793
|
FINISHED |
| Object | limited public transport |
—
|
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: limited public transport | Statement: [Lundie, hasTransportCharacter, limited public transport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTransportCharacter Context triple: [Lundie, hasTransportCharacter, limited public transport]
-
A.
hasTransportCode
Indicates that an entity is associated with a specific transport-related code used to identify or classify its mode, method, or details of transportation.
-
B.
hasTransportCategory
Indicates that one entity is classified under a particular category or type of transport associated with another entity.
-
C.
hasTransportFunction
Indicates that an entity serves to move or carry something (such as people, goods, or signals) from one place or state to another.
-
D.
hasLanguageCharacter
Indicates that an entity uses, contains, or is associated with a specific written or symbolic character from a language.
-
E.
transportsCharacter
Indicates that one entity moves or carries a character from one location or state to another.
- 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_69d8d38bbe7c8190bdec3138e7d413c9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54d04bdc48190b0213132923a7580 |
completed | April 19, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69e478cf5e888190a0b1074b0c6525df |
completed | April 19, 2026, 6:40 a.m. |
| PDg | Predicate description generation | batch_69e484121cd48190bf583b4c94636a30 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 11:45 a.m.