Triple
T33202544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Munna (Rangeela) |
E849940
|
entity |
| Predicate | hasUnspokenLoveFor |
P95052
|
FINISHED |
| Object | Mili (Rangeela) |
—
|
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: Mili (Rangeela) | Statement: [Munna (Rangeela), hasUnspokenLoveFor, Mili (Rangeela)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnspokenLoveFor Context triple: [Munna (Rangeela), hasUnspokenLoveFor, Mili (Rangeela)]
-
A.
rumoredLoverOf
Indicates that one entity is widely believed or speculated to be the romantic partner or lover of another entity, without confirmed evidence.
-
B.
hasLoveLifeCharacteristic
Indicates that an entity possesses a particular quality, status, or attribute related to its romantic or love life.
-
C.
hasRumoredSubtext
Indicates that something is believed or speculated to contain an implied or hidden meaning that is not explicitly stated.
-
D.
fellInLoveWith
chosen
Indicates that one entity developed romantic love or deep affectionate feelings toward another entity.
-
E.
hasYoungLoverCharacter
Indicates that an entity is involved in a romantic or intimate relationship with a significantly younger lover character.
- 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_69f3495efedc8190843a5728089544b9 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fbc9d1dba881908c399b8e1dc13ce2 |
completed | May 6, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
Created at: May 1, 2026, 1:30 a.m.