Triple
T37152030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gru’s laboratory |
E920386
|
entity |
| Predicate | hasScientist |
P151029
|
FINISHED |
| Object | Dr. Nefario |
—
|
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: Dr. Nefario | Statement: [Gru’s laboratory, hasScientist, Dr. Nefario]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScientist Context triple: [Gru’s laboratory, hasScientist, Dr. Nefario]
-
A.
hasScientificRole
Indicates that an entity holds or performs a specific scientific position, function, or responsibility in relation to another entity or context.
-
B.
hasHumanScientistCharacter
chosen
Indicates that an entity includes or features a character who is a human scientist.
-
C.
hasScientificLegacy
Indicates that an entity has left a lasting, influential impact on scientific knowledge, methods, or practice that continues beyond its original context or time.
-
D.
producedScientist
Indicates that an entity (such as an institution, organization, or place) has produced, trained, or given rise to a particular scientist.
-
E.
hasScience
Indicates that an entity possesses, includes, or is associated with a particular scientific discipline, content, or attribute.
- 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_69f76e9f87c08190b4c8f7fafbd8345a |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd7fdafbe881908a31fcb407af2c34 |
completed | May 8, 2026, 6:16 a.m. |
| PD | Predicate disambiguation | batch_69fd7ef0ea908190b5d83f71565bdb1c |
completed | May 8, 2026, 6:13 a.m. |
Created at: May 3, 2026, 4:15 p.m.