Triple
T26387100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OKBOMB |
E663309
|
entity |
| Predicate | relatedToBuilding |
P37
|
FINISHED |
| Object | Alfred P. Murrah Federal Building |
—
|
NE NERFINISHED |
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: Alfred P. Murrah Federal Building | Statement: [OKBOMB, relatedToBuilding, Alfred P. Murrah Federal Building]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedToBuilding Context triple: [OKBOMB, relatedToBuilding, Alfred P. Murrah Federal Building]
-
A.
attachedBuilding
Indicates that one building is physically connected to or joined with another building as part of the same structural complex.
-
B.
refersToBuildingOn
Indicates that one entity explicitly references or designates a specific building as its subject or target.
-
C.
belongsToBuildingComplex
Indicates that one building or structure is part of, or included within, a larger building complex.
-
D.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
E.
appliedToBuilding
Indicates that something (such as a process, treatment, regulation, or attribute) is directed toward, implemented on, or otherwise affects a building.
- 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_69ee88374adc81909868f3bab374a32f |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69fe5ec9028081909ae3d6fbe2f4cbbc |
completed | May 8, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69fe5e1d715881909fc516fafc707644 |
completed | May 8, 2026, 10:05 p.m. |
Created at: April 26, 2026, 11:23 p.m.