Triple
T36785865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NSEA Protector |
E908908
|
entity |
| Predicate | NTEMeaning |
P186297
|
FINISHED |
| Object | Not The Enterprise |
—
|
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: Not The Enterprise | Statement: [NSEA Protector, NTEMeaning, Not The Enterprise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NTEMeaning Context triple: [NSEA Protector, NTEMeaning, Not The Enterprise]
-
A.
etMeaning
Indicates that one entity expresses or conveys the semantic content or intended sense of another entity (such as a word, phrase, or symbol).
-
B.
tegMeaning
Indicates that one entity expresses, conveys, or stands for the meaning or semantic content of another entity.
-
C.
textMeaning
Indicates that one text expresses, conveys, or corresponds to a particular meaning or semantic content.
-
D.
stringMeaning
Indicates that one entity represents the semantic content or interpretation of a given string associated with another entity.
-
E.
letterMeaning
Indicates that a particular letter conveys a specific meaning, interpretation, or semantic content.
- F. None of above. chosen
Provenance (4 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_69f76e7a937c81909ed7359641e670f6 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7cabdd2d88190be1c8de7e499cb83 |
completed | May 3, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69f7c89b528c8190bf80b230fc7c7108 |
completed | May 3, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69f7ca91f1808190b2a05c4b691da0bb |
completed | May 3, 2026, 10:22 p.m. |
Created at: May 3, 2026, 4:12 p.m.