Triple
T18928282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ostrów Tumski (Wrocław) |
E463031
|
entity |
| Predicate | hasStreetLightingTradition |
P19423
|
FINISHED |
| Object | gas lanterns lit by lamplighter |
—
|
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: gas lanterns lit by lamplighter | Statement: [Ostrów Tumski (Wrocław), hasStreetLightingTradition, gas lanterns lit by lamplighter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStreetLightingTradition Context triple: [Ostrów Tumski (Wrocław), hasStreetLightingTradition, gas lanterns lit by lamplighter]
-
A.
hasHistoricStreet
Indicates that an entity is associated with or located on a street that has recognized historical significance.
-
B.
hasTraditionIn
chosen
Indicates that a particular tradition, custom, or longstanding practice is present, observed, or established within a specified place, group, or context.
-
C.
hasStreetcarHistory
Indicates that there is a historical association or past involvement with streetcars or streetcar systems.
-
D.
hasTreeLinedStreets
Indicates that the streets in a given area are lined or bordered with trees along their sides.
-
E.
previousLightStations
Indicates that one light station existed earlier in time or sequence than another related light station.
- 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_69d8dcfdbbb881909964fa5a75bd0b48 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c9bdddb481908bebd32f927ed5de |
completed | April 20, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69e4a2efec5c8190840704016bf547a1 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 11:59 a.m.