Triple
T3502192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tower 2 |
E73993
|
entity |
| Predicate | hasEmergencyStairwells |
P48544
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Tower 2, hasEmergencyStairwells, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmergencyStairwells Context triple: [Tower 2, hasEmergencyStairwells, yes]
-
A.
hasEmergencyExits
Indicates that an entity is equipped with designated emergency exits for use during urgent or hazardous situations.
-
B.
hasStairway
Indicates that one entity includes or is connected to another entity by a stairway providing vertical access between levels.
-
C.
hasEscalators
Indicates that one entity is equipped with or contains escalators that can be used for movement between different levels or areas.
-
D.
numberOfEmergencyExits
Indicates the quantity of emergency exits associated with an entity or location.
-
E.
hasEmergencySystems
Indicates that the subject is equipped with or includes systems designed to detect, respond to, or manage emergency situations.
- 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbef47988190b5b3fe2e452b9ac8 |
completed | March 8, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_69adae0cd8b0819099da300af09880da |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adaef1037c819082c7af949ec85360 |
completed | March 8, 2026, 5:16 p.m. |
Created at: March 8, 2026, 3:18 p.m.