Triple
T7455162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rakhigarhi |
E172103
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
mound RGR-2
Mound RGR-2 is one of the principal archaeological mounds at the Indus Valley Civilization site of Rakhigarhi in Haryana, India, containing important remains from this ancient urban settlement.
|
E665291
|
NE FINISHED |
How this triple was built (4 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: mound RGR-2 | Statement: [Rakhigarhi, hasPart, mound RGR-2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: mound RGR-2 Context triple: [Rakhigarhi, hasPart, mound RGR-2]
-
A.
GR-42
GR-42 is the ISO 3166-2 subdivision code assigned to the Larissa regional unit in Greece.
-
B.
GR-61
GR-61 is the ISO 3166-2 subdivision code assigned to the Pieria regional unit in Greece.
-
C.
M-24
M-24 is a state highway in Michigan that serves as a key north–south transportation route through communities such as Orion Township.
-
D.
MR-73
MR-73 is a class of rubber-tired electric multiple unit trains used on the Montreal Metro system.
-
E.
M-153
M-153 is a state trunkline highway in Michigan, commonly known as Ford Road, that serves as a major east–west arterial route through the Detroit metropolitan area.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: mound RGR-2 Triple: [Rakhigarhi, hasPart, mound RGR-2]
Generated description
Mound RGR-2 is one of the principal archaeological mounds at the Indus Valley Civilization site of Rakhigarhi in Haryana, India, containing important remains from this ancient urban settlement.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: mound RGR-2 Target entity description: Mound RGR-2 is one of the principal archaeological mounds at the Indus Valley Civilization site of Rakhigarhi in Haryana, India, containing important remains from this ancient urban settlement.
-
A.
GR-42
GR-42 is the ISO 3166-2 subdivision code assigned to the Larissa regional unit in Greece.
-
B.
GR-61
GR-61 is the ISO 3166-2 subdivision code assigned to the Pieria regional unit in Greece.
-
C.
M-24
M-24 is a state highway in Michigan that serves as a key north–south transportation route through communities such as Orion Township.
-
D.
MR-73
MR-73 is a class of rubber-tired electric multiple unit trains used on the Montreal Metro system.
-
E.
M-153
M-153 is a state trunkline highway in Michigan, commonly known as Ford Road, that serves as a major east–west arterial route through the Detroit metropolitan area.
- F. None of above. chosen
Provenance (5 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_69c68a66554c8190add75c65942c0317 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f3addd648190b618bfbffe08db2c |
completed | March 27, 2026, 9:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c827bedc408190a9a77f293fb12762 |
completed | March 28, 2026, 7:10 p.m. |
| NEDg | Description generation | batch_69c8290c62d0819080a1e1820364da88 |
completed | March 28, 2026, 7:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c82958eddc8190ad1697969241ec39 |
completed | March 28, 2026, 7:17 p.m. |
Created at: March 27, 2026, 3:15 p.m.