Triple
T13016018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kendra Dumbledore |
E322552
|
entity |
| Predicate | tombInscription |
P57501
|
FINISHED |
| Object | “Where your treasure is, there will your heart be also” |
—
|
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: “Where your treasure is, there will your heart be also” | Statement: [Kendra Dumbledore, tombInscription, “Where your treasure is, there will your heart be also”]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tombInscription Context triple: [Kendra Dumbledore, tombInscription, “Where your treasure is, there will your heart be also”]
-
A.
hasGraveInscription
chosen
Indicates that an entity (typically a grave or tomb) bears a specific inscription engraved or written on it.
-
B.
pyramidTextInscriptions
Indicates that the subject has text inscriptions located on or within a pyramid.
-
C.
materialTypicallyInscribedOn
Indicates the material that is most commonly used as the surface or medium on which something is inscribed.
-
D.
inscriptionsFoundAt
Indicates that inscriptions are discovered or located at a particular place or site.
-
E.
scriptOfInscription
Indicates the writing system or script in which a given inscription is written.
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97ecd04748190ade2530ee5db35fe |
completed | April 10, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69d97dc39a0881908119c62e31bf6182 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:50 p.m.