Triple
T29135326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | She Who Gives Birth but Was Herself Not Born |
E738497
|
entity |
| Predicate | highlightsStatus |
P3362
|
FINISHED |
| Object | Mut as primordial being |
—
|
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: Mut as primordial being | Statement: [She Who Gives Birth but Was Herself Not Born, highlightsStatus, Mut as primordial being]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: highlightsStatus Context triple: [She Who Gives Birth but Was Herself Not Born, highlightsStatus, Mut as primordial being]
-
A.
highlightsSign
Indicates that one entity visually emphasizes or draws special attention to a sign.
-
B.
highlights
chosen
Indicates that one entity draws special attention to, emphasizes, or visually marks another entity as important or noteworthy.
-
C.
highlightsAttributeOf
Indicates that one entity draws attention to, emphasizes, or showcases a particular attribute or property of another entity.
-
D.
hasHighlightGoal
Indicates that an entity has a primary or emphasized goal that is singled out as especially important or noteworthy.
-
E.
hasHighPointStatus
Indicates that an entity holds a high or elevated status within a point-based or ranking system.
- 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_69f07cb3adb48190a9e0e169cd026634 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f6623013c88190a87411424f9af256 |
completed | May 2, 2026, 8:44 p.m. |
| PD | Predicate disambiguation | batch_69f65c2376a08190be5215171e908e69 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 11:34 a.m.