Triple
T37303514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Talos I |
E926018
|
entity |
| Predicate | researchFocusInFiction |
P52272
|
FINISHED |
| Object | Typhon organisms |
—
|
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: Typhon organisms | Statement: [Talos I, researchFocusInFiction, Typhon organisms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: researchFocusInFiction Context triple: [Talos I, researchFocusInFiction, Typhon organisms]
-
A.
fictionalFocus
Indicates that the primary emphasis or attention within a context is placed on fictional content, elements, or aspects.
-
B.
fieldOfExpertiseInFiction
chosen
Indicates that a fictional character or entity is portrayed as having specialized knowledge, skill, or professional focus in a particular field or domain.
-
C.
workInFiction
Indicates that one entity is a fictional work in which the other entity appears or is set.
-
D.
functionInLiterature
Indicates that one entity serves a particular narrative, rhetorical, or thematic role within a literary work in relation to another entity.
-
E.
literarySubject
Indicates that one entity serves as the subject, topic, or focus of a literary work created by 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_69f76eb1bc508190924e9fa5d8acdeb3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb78cbef988190b8f79d946b46e6b2 |
completed | May 6, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69fb5a9ac5a08190b24ef308963fc52b |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:16 p.m.