Triple
T29100851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shin Megami Tensei |
E736635
|
entity |
| Predicate | alignmentTypes |
P59151
|
FINISHED |
| Object | Law |
—
|
NE NERFINISHED |
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: Law | Statement: [Shin Megami Tensei, alignmentTypes, Law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alignmentTypes Context triple: [Shin Megami Tensei, alignmentTypes, Law]
-
A.
alignsWith
Indicates that one entity is in agreement, harmony, or consistent correspondence with another in terms of position, direction, standard, or principle.
-
B.
alignmentInSeries
Indicates that one entity’s position or orientation is arranged in a specific way relative to others within an ordered sequence or series.
-
C.
alignmentMethod
Indicates the technique or procedure used to align one entity with another or with a reference standard.
-
D.
alignmentComponents
Indicates that one entity is composed of or associated with specific subparts or elements that together form its overall alignment.
-
E.
hasAlignmentType
chosen
Indicates that an entity possesses a specific alignment category or classification, such as moral, structural, or directional alignment.
- 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_69f077ec765c81909474c88bcc8bab43 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f661b58ac48190907b6c6e9ccc2c59 |
completed | May 2, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69f65c2376a08190be5215171e908e69 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 11:12 a.m.