Triple
T38111288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marunouchi Building |
E951660
|
entity |
| Predicate | hasFireSafetyDesign |
P63490
|
FINISHED |
| Object | earthquake-resistant |
—
|
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: earthquake-resistant | Statement: [Marunouchi Building, hasFireSafetyDesign, earthquake-resistant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFireSafetyDesign Context triple: [Marunouchi Building, hasFireSafetyDesign, earthquake-resistant]
-
A.
hasSafetyDesignation
Indicates that an entity has been assigned a specific safety-related classification or status.
-
B.
hasSafetyCharacteristic
chosen
Indicates that an entity possesses a specific safety-related property, feature, or attribute.
-
C.
hasSafetyRegulationCompliance
Indicates that an entity adheres to, satisfies, or is in conformity with specified safety regulations or standards.
-
D.
usesSafetySystemsFrom
Indicates that one entity employs or relies on the safety systems that originate from or are provided by another entity.
-
E.
hasSafetyCertificate
Indicates that an entity possesses or has been granted a valid safety certificate.
- 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_69f76f065ed08190bdfb1b6d817f5b39 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a007dd341108190a1d03eab46041694 |
completed | May 10, 2026, 12:45 p.m. |
| PD | Predicate disambiguation | batch_6a007b1fe2a881909ec50a1e65e4651b |
completed | May 10, 2026, 12:33 p.m. |
Created at: May 3, 2026, 4:21 p.m.