Triple
T11997172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Montague |
E285560
|
entity |
| Predicate | scenePresence |
P102598
|
FINISHED |
| Object | Act 1, Scene 1 |
—
|
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: Act 1, Scene 1 | Statement: [Lady Montague, scenePresence, Act 1, Scene 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scenePresence Context triple: [Lady Montague, scenePresence, Act 1, Scene 1]
-
A.
mediaPresence
Indicates the extent to which something is visible, represented, or covered within various media channels or platforms.
-
B.
airPresence
Indicates that air is present in or around an entity, typically signifying that the entity contains, is surrounded by, or is exposed to air.
-
C.
globalPresence
Indicates that an entity operates, is represented, or has a significant footprint across multiple countries or world regions.
-
D.
statePresence
Indicates that an entity exists, operates, or is present within a particular state or governmental jurisdiction.
-
E.
hasHumanPresence
Indicates that humans are physically present in or occupying a given location, object, or context.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903c172788190b92042e9d10a48bf |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902b245cc8190af96a9c2bd9c6250 |
completed | April 10, 2026, 2:01 p.m. |
| PDg | Predicate description generation | batch_69d9038e39f881908c58c19802ba2eb0 |
completed | April 10, 2026, 2:05 p.m. |
Created at: April 8, 2026, 9:46 p.m.