Triple
T36536820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San al-Hagar (Tanis) |
E900607
|
entity |
| Predicate | reusesMonumentsFrom |
P185824
|
FINISHED |
| Object | Pi-Ramesses |
—
|
NE NERFINISHED |
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: Pi-Ramesses | Statement: [San al-Hagar (Tanis), reusesMonumentsFrom, Pi-Ramesses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reusesMonumentsFrom Context triple: [San al-Hagar (Tanis), reusesMonumentsFrom, Pi-Ramesses]
-
A.
originalMonumentsFrom
Indicates that certain monuments were originally created, erected, or located in a specified place or source region.
-
B.
eraOfOriginalMonuments
Indicates the historical time period during which the original monuments were created or first established.
-
C.
usedInMonument
Indicates that something serves as a material, component, or element incorporated into the construction or design of a monument.
-
D.
scriptUsedInMonuments
Indicates that a particular writing system or script is employed in the inscriptions or textual elements found on specific monuments.
-
E.
builtMonument
Indicates that one entity constructed or created a monument in honor of, or related to, another entity.
- 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_69f76e5fbb388190b70c4c15573c8143 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b91fd88190ab85afd626603769 |
completed | May 3, 2026, 9:44 p.m. |
| PDg | Predicate description generation | batch_69f7c3705b5c81908c84004543a71c07 |
completed | May 3, 2026, 9:51 p.m. |
Created at: May 3, 2026, 4:11 p.m.