Triple
T9119020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrityu |
E218796
|
entity |
| Predicate | oftenPersonifiedAs |
P18297
|
FINISHED |
| Object | deity-like figure |
—
|
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: deity-like figure | Statement: [Mrityu, oftenPersonifiedAs, deity-like figure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenPersonifiedAs Context triple: [Mrityu, oftenPersonifiedAs, deity-like figure]
-
A.
isPersonificationOf
Indicates that one entity represents or embodies an abstract concept, quality, or non-human thing in human form.
-
B.
oftenDepictedAs
chosen
Indicates that one entity is frequently represented or portrayed in the form, appearance, or symbolism of another entity.
-
C.
oftenSays
Indicates that one entity frequently makes a particular statement or remark, or regularly expresses a certain idea or phrase.
-
D.
namedAfterFictionalCharacter
Indicates that one entity has been given its name in honor of, or derived from, a fictional character.
-
E.
oftenBroadcastAs
Indicates that something is frequently transmitted or aired through a broadcast medium under a particular form, title, or version.
- 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_69ca83dddd548190983b96c664f7f367 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8a7c6d48190a015efd17a017ca1 |
completed | April 1, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69cc66003e3c819091e1e42c9cf7c781 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:17 p.m.