Triple
T33439560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marian apparitions of 1877 |
E856322
|
entity |
| Predicate | hasOtherSeerAgeAtTime |
P176627
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Marian apparitions of 1877, hasOtherSeerAgeAtTime, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOtherSeerAgeAtTime Context triple: [Marian apparitions of 1877, hasOtherSeerAgeAtTime, 12]
-
A.
existsInAge
Indicates that an entity is present, valid, or active during a specified age or time period.
-
B.
hasYoungerSelfIn
Indicates that an entity is related to another entity representing its own younger version within a specified context or time frame.
-
C.
hasRelativeAge
Indicates that one entity has an age that is defined or compared in relation to the age of another entity.
-
D.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
E.
hasApproximateAgeRange
Indicates that one entity is associated with another entity representing an estimated or non-exact span of ages.
- 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_69f34971b75881908be360bb041f003c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e52a6d40819084472f6072c91e9f |
completed | May 3, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69f6e3da41948190a4cfe866ce184f73 |
completed | May 3, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69f6e47c13348190a10528c84a401178 |
completed | May 3, 2026, 6 a.m. |
Created at: May 1, 2026, 1:37 a.m.