Triple
T29386899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Groke |
E745276
|
entity |
| Predicate | hasDeeperMeaning |
P10718
|
FINISHED |
| Object | commentary on emotional neglect |
—
|
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: commentary on emotional neglect | Statement: [The Groke, hasDeeperMeaning, commentary on emotional neglect]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDeeperMeaning Context triple: [The Groke, hasDeeperMeaning, commentary on emotional neglect]
-
A.
hasUprightMeaning
Indicates that something possesses a figurative or symbolic meaning associated with being upright, such as moral integrity, correctness, or proper orientation.
-
B.
hasIronicMeaning
Indicates that something conveys a meaning opposite to or incongruent with its literal expression, creating an ironic effect.
-
C.
hasMultipleMeanings
Indicates that a term, symbol, or expression is associated with more than one distinct meaning or interpretation.
-
D.
possibleMeaning
chosen
Indicates that something may plausibly represent, signify, or be interpreted as a particular meaning or sense.
-
E.
hasMeaningInOriginLanguage
Indicates that something (such as a word, phrase, or symbol) possesses a specific meaning in its original or source language.
- 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_69f0a79cfd5481909b4dde750cb8d2c6 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fd3d46d1f48190a1b20dd063224b7d |
completed | May 8, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69fd3ae1510c81908fe1280efc17feee |
completed | May 8, 2026, 1:22 a.m. |
Created at: April 28, 2026, 2:39 p.m.