Triple
T17640292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Where the Pavement Ends |
E429204
|
entity |
| Predicate | runtimeStatus |
P128361
|
FINISHED |
| Object | partially lost film |
—
|
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: partially lost film | Statement: [Where the Pavement Ends, runtimeStatus, partially lost film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runtimeStatus Context triple: [Where the Pavement Ends, runtimeStatus, partially lost film]
-
A.
automationStatus
Indicates whether a process, task, or system is being performed automatically or requires manual intervention.
-
B.
programStatus
Indicates the current state or condition of a program within its lifecycle (e.g., planned, active, paused, completed, or terminated).
-
C.
actualStatus
Indicates the current, real-world state or condition of an entity, as opposed to a planned, expected, or nominal status.
-
D.
resourceStatus
Indicates the current condition or state of availability, usability, or operational readiness of a given resource.
-
E.
trainingStatus
Indicates the current state or phase of an entity within a training or learning process.
- 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_69d889e2c2608190b762e76d9b2262f1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46de50bf481909e938613b38f0202 |
completed | April 19, 2026, 5:53 a.m. |
| PD | Predicate disambiguation | batch_69e3cddc87188190ac2f049b86038676 |
completed | April 18, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 6:02 a.m.