Triple
T10106253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cross in the Mountains |
E216328
|
entity |
| Predicate | hasFrame |
P76579
|
FINISHED |
| Object | ornate gilded frame with Christian symbols |
—
|
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: ornate gilded frame with Christian symbols | Statement: [Cross in the Mountains, hasFrame, ornate gilded frame with Christian symbols]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFrame Context triple: [Cross in the Mountains, hasFrame, ornate gilded frame with Christian symbols]
-
A.
hasFrameType
chosen
Indicates that an entity possesses or is associated with a specific type or category of frame.
-
B.
hasFrameFinish
Indicates that an entity’s frame possesses a specific surface treatment or finish.
-
C.
hasFiber
Indicates that one entity contains, includes, or is characterized by a certain amount or type of fiber.
-
D.
hasFramingDevice
Indicates that one entity serves as a narrative or structural framing device that contextualizes, introduces, or encloses the main content of another entity.
-
E.
hasFront
Indicates that an entity possesses or is associated with a front-facing side, surface, or portion.
- 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_69ca83d039f08190b9d10363221c69fb |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd0c8a0408190be886ec1013a5208 |
completed | April 2, 2026, 2:13 a.m. |
| PD | Predicate disambiguation | batch_69cd4b9b853c8190a2af993ce9b21309 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:03 p.m.