Triple
T1950254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Almighty |
E42141
|
entity |
| Predicate | equivalentTermIn |
P28329
|
FINISHED |
| Object | Hebrew El Shaddai |
—
|
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: Hebrew El Shaddai | Statement: [Almighty, equivalentTermIn, Hebrew El Shaddai]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equivalentTermIn Context triple: [Almighty, equivalentTermIn, Hebrew El Shaddai]
-
A.
equivalentTo
Indicates that two entities represent the same concept, value, or state, and can be treated as interchangeable in the given context.
-
B.
equivalentInTibet
Indicates that two entities are considered equivalent or correspond to each other within the context of Tibet.
-
C.
languageEquivalent
chosen
Indicates that two linguistic expressions convey the same meaning or function across different languages or language varieties.
-
D.
equivalentInZapotec
Indicates that two linguistic elements are equivalent in meaning or function within the Zapotec language.
-
E.
languageTerm
Indicates that one entity is a linguistic expression (word, phrase, or term) used to denote or label the other 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_69a8870e08fc8190a319cbf2600db15f |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb332b014819085bfc88d66cfc10a |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abaff3eda88190b643994cb4dfb8df |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.