Triple
T29082477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meredith Quill |
E734015
|
entity |
| Predicate | romanticEncounterLocation |
P61227
|
FINISHED |
| Object | Missouri Dairy Queen parking lot |
—
|
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: Missouri Dairy Queen parking lot | Statement: [Meredith Quill, romanticEncounterLocation, Missouri Dairy Queen parking lot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: romanticEncounterLocation Context triple: [Meredith Quill, romanticEncounterLocation, Missouri Dairy Queen parking lot]
-
A.
romanticSceneWith
Indicates a scene or situation in which the two entities are engaged together in a romantic context or interaction.
-
B.
rendezvousWith
Indicates that two or more entities meet or come together at an agreed place and time, often for a specific purpose.
-
C.
romanticPlotFunction
Indicates a narrative relationship where characters are involved in or contribute to a romantic storyline or romantic development within the plot.
-
D.
romanticOutcome
Indicates that a romantic relationship or interaction between entities results in a particular outcome, such as success, failure, or change in status.
-
E.
firstMeetingPlace
chosen
Indicates the location where two or more entities met each other for the very first time.
- 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_69f05b0c0f28819086eae6e84f2ae472 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f67d3624248190a36a9b2d2e9778d4 |
completed | May 2, 2026, 10:39 p.m. |
| PD | Predicate disambiguation | batch_69f678ce54b081908c26edfd49e39c60 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 28, 2026, 10:56 a.m.