Triple
T15672279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nemean Lion |
E377343
|
entity |
| Predicate | skinWas |
P8035
|
FINISHED |
| Object | impervious to weapons |
—
|
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: impervious to weapons | Statement: [Nemean Lion, skinWas, impervious to weapons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skinWas Context triple: [Nemean Lion, skinWas, impervious to weapons]
-
A.
skinCharacteristic
chosen
Indicates a relationship where an entity is associated with a particular quality, feature, or condition of its skin.
-
B.
bodyTreatment
Indicates a treatment or therapeutic procedure that is applied to a person's body.
-
C.
focusesOnSkinConcern
Indicates that something (such as a product, treatment, or content) is specifically directed toward addressing or improving a particular skin concern.
-
D.
skinThickness
Indicates the measured thickness of an entity’s skin, typically quantifying how thick its outer tissue layer is.
-
E.
fleshColor
Indicates the color or hue of an entity’s flesh or skin.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f13b1b08190beabc9f4098aa096 |
completed | April 16, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69deda8b36a4819081cb5708fe77ef51 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:16 a.m.