Triple
T9240498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tekhnopark |
E222044
|
entity |
| Predicate | hasNumberOfExits |
P87730
|
FINISHED |
| Object | several pedestrian exits |
—
|
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: several pedestrian exits | Statement: [Tekhnopark, hasNumberOfExits, several pedestrian exits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfExits Context triple: [Tekhnopark, hasNumberOfExits, several pedestrian exits]
-
A.
hasExitFor
Indicates that something provides or includes a specific exit intended for a particular destination, purpose, or user.
-
B.
hasNumberOfEntrances
Indicates the relationship that specifies how many entrances an entity possesses.
-
C.
hasExits
Indicates that an entity provides one or more ways out or routes leading from it to other locations or states.
-
D.
hasMultipleEntrances
Indicates that an entity possesses more than one distinct entrance or access point.
-
E.
exitsThrough
Indicates that an entity leaves or departs from a place, structure, or area by passing through a specified exit or passage.
- 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_69ca83ee26cc81909ac624e190597d6d |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccf0a3888c8190b72d8d0b850bdfbc |
completed | April 1, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69cc7a4765648190aa9445c4a22dc471 |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc95597be081908ece2491dd2f0f74 |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:30 p.m.