Triple
T21252260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spider-Army |
E523772
|
entity |
| Predicate | enemy |
P4567
|
FINISHED |
| Object | Morlun |
—
|
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: Morlun | Statement: [Spider-Army, enemy, Morlun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morlun Context triple: [Spider-Army, enemy, Morlun]
-
A.
Morlun
chosen
Morlun is a powerful, vampiric multiversal predator in Marvel Comics best known as one of Spider-Man’s most dangerous and relentless foes.
-
B.
Ilmorog
Ilmorog is a fictional rural Kenyan village that serves as the central backdrop for Ngũgĩ wa Thiong’o’s novel "Petals of Blood," symbolizing the impacts of colonialism and postcolonial change.
-
C.
Ilmorog
Ilmorog is a fictional rural Kenyan village depicted in Ngũgĩ wa Thiong’o’s novel "Devil on the Cross," symbolizing the struggles and resistance of the oppressed under neocolonial capitalism.
-
D.
Gursken
Gursken is a small coastal village in Sande municipality in Møre og Romsdal county, Norway.
-
E.
Mulciber
Mulciber is a Death Eater from the Harry Potter series, known for his skill with the Imperius Curse and his imprisonment after Voldemort’s first downfall.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b5146c108190adc9adb73e90abff |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7359f5b408190b951adddba83c97a |
completed | April 21, 2026, 8:30 a.m. |
Created at: April 16, 2026, 3:57 p.m.