Triple
T15904617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lt. Mark Rumsfield |
E385676
|
entity |
| Predicate | hasCharacteristicProp |
P274
|
FINISHED |
| Object | wears military-style clothing |
—
|
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: wears military-style clothing | Statement: [Lt. Mark Rumsfield, hasCharacteristicProp, wears military-style clothing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCharacteristicProp Context triple: [Lt. Mark Rumsfield, hasCharacteristicProp, wears military-style clothing]
-
A.
hasCharacteristic
chosen
Indicates that an entity possesses, exhibits, or is defined by a particular attribute, feature, or quality.
-
B.
hasCharacteristicArtifact
Indicates that an entity is associated with a specific artifact that characterizes, exemplifies, or is typical of it.
-
C.
eraCharacteristic
Indicates that a particular quality, feature, or attribute is characteristic of, or typically associated with, a given historical or temporal era.
-
D.
hasNameCharacteristic
Indicates that an entity possesses a specific quality or attribute related to its name.
-
E.
maskCharacteristic
Indicates that one entity serves to conceal, obscure, or alter the apparent characteristics or properties of another entity.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142ca3b208190946c3aa4c1e6087c |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:52 a.m.