Triple
T10935354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reverend Mr. Hooper |
E258317
|
entity |
| Predicate | veilCovers |
P87207
|
FINISHED |
| Object | his face except his mouth and chin |
—
|
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: his face except his mouth and chin | Statement: [Reverend Mr. Hooper, veilCovers, his face except his mouth and chin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: veilCovers Context triple: [Reverend Mr. Hooper, veilCovers, his face except his mouth and chin]
-
A.
veilCustom
Indicates a customary or traditional practice involving the wearing or use of a veil.
-
B.
veilName
Indicates that an entity is associated with or identified by a particular veil-related name or alias.
-
C.
coverUpBy
Indicates that one entity conceals, suppresses, or hides the actions, information, or wrongdoing associated with another entity.
-
D.
bodyCoverage
chosen
Indicates the extent or proportion of an entity’s body that is covered by another substance, material, or feature.
-
E.
bodyCovering
Indicates the type of external covering or surface (such as skin, fur, feathers, or scales) that characterizes an entity’s body.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770aee178819082c1671a37ff7d82 |
completed | April 9, 2026, 9:26 a.m. |
| PD | Predicate disambiguation | batch_69d72e816a98819096d6c10dfb88a66a |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:23 p.m.