Triple
T7841667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julian Morgenstern |
E181817
|
entity |
| Predicate | isFictionalCounterpartOf |
P60815
|
FINISHED |
| Object | Shadowhunter order member |
—
|
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: Shadowhunter order member | Statement: [Julian Morgenstern, isFictionalCounterpartOf, Shadowhunter order member]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFictionalCounterpartOf Context triple: [Julian Morgenstern, isFictionalCounterpartOf, Shadowhunter order member]
-
A.
fictionalStandInFor
chosen
Indicates that one entity serves as a fictional or symbolic substitute representing another real or implied entity.
-
B.
fictionalCharacter
Indicates that one entity is a fictional character that appears within the narrative world of another entity (such as a work, series, or franchise).
-
C.
ownedByFictionalCharacter
Indicates that something is possessed or owned by a fictional (not real-world) character.
-
D.
hasFictionalLeader
Indicates that an entity is led or governed by a leader who is a fictional character rather than a real person.
-
E.
residesInFictionalLocation
Indicates that an entity lives or is based in a location that is explicitly fictional or imaginary.
- 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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb14c6cbe48190b73df491de1004c3 |
completed | March 31, 2026, 12:26 a.m. |
| PD | Predicate disambiguation | batch_69cae91e98988190abd4ece75932c589 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:47 p.m.