Triple
T17912149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alan Scott |
E447840
|
entity |
| Predicate | firstAppearanceMonth |
P129291
|
FINISHED |
| Object | July |
—
|
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: July | Statement: [Alan Scott, firstAppearanceMonth, July]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstAppearanceMonth Context triple: [Alan Scott, firstAppearanceMonth, July]
-
A.
firstAppeared
Indicates the earliest known time or context in which an entity was introduced, observed, or came into existence.
-
B.
firstAppearedAt
Indicates the point in time or specific event at which an entity was first introduced, observed, or became known.
-
C.
firstAppearanceMa
Indicates that an entity (such as a character or item) makes its first appearance in a specific manga.
-
D.
firstAppearanceApprox
Indicates that one entity is the approximate or estimated first appearance of another entity in time or context.
-
E.
firstAppearanceFor
Indicates that an entity marks the initial occurrence or debut of another entity within a given context or medium.
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49ea0ea008190b54a999e0704fb67 |
completed | April 19, 2026, 9:21 a.m. |
| PD | Predicate disambiguation | batch_69e3d8ec2f6881909d7f54b878cbed37 |
completed | April 18, 2026, 7:18 p.m. |
| PDg | Predicate description generation | batch_69e3db77df0c819084548168c62b398c |
completed | April 18, 2026, 7:28 p.m. |
Created at: April 10, 2026, 10:19 a.m.