Triple
T11037542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | False Dmitry III |
E260924
|
entity |
| Predicate | numberOfMainImpostors |
P97427
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [False Dmitry III, numberOfMainImpostors, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMainImpostors Context triple: [False Dmitry III, numberOfMainImpostors, 3]
-
A.
numberOfInvaders
Indicates the quantity of entities classified as invaders associated with a given subject or context.
-
B.
numberOfMainDetectors
Indicates the quantity of primary detectors associated with or used in a given context or system.
-
C.
numberOfMainElements
Indicates the quantity of primary or central elements associated with an entity or structure.
-
D.
numberOfMainPerformers
Indicates the count of primary performers involved in a performance or event.
-
E.
numberOfPerpetrators
Indicates the count of distinct individuals who carried out or participated in a particular act, event, or offense.
- 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797fd5fe081908af13835b18de7b8 |
completed | April 9, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69d74407cb088190ba37c8da3d342b64 |
completed | April 9, 2026, 6:15 a.m. |
| PDg | Predicate description generation | batch_69d750c99f9881908ee2b01b6ce4b3a1 |
completed | April 9, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:25 p.m.